Sugar-free seedling culture carbon dioxide monitoring system and regulation method

Abstract

The application discloses a sugar-free seedling culture carbon dioxide monitoring system and a regulation method, belongs to the technical field of intelligent regulation of seedling culture, and aims to solve the problems of uneven distribution of carbon dioxide concentration, poor dynamic adaptability of supply and demand in sugar-free seedling culture. The distributed grid nodes collect the carbon dioxide concentration and environmental parameters, judge the concentration distribution state, construct the concentration field through layered interpolation when potential unevenness occurs, identify the abnormal area and solve the target parameters of the air vent and the fan; a seedling environmental demand model library is constructed, the concentration interval is corrected according to the demand parameters and the environmental parameters, and the target concentration is positioned; combined with the concentration deviation value, the space and the ventilation coefficient, the regulation parameters of the carbon dioxide supply unit are updated, and the abnormal monitoring and optimization feedback are simultaneously performed. The accurate regulation and dynamic adaptation of the carbon dioxide concentration are realized, the stability and resource utilization efficiency of the seedling culture environment are improved, and the growth quality of the seedlings in the sugar-free culture is ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of seedling culture intelligent regulation, more particularly to a carbon dioxide monitoring system and regulation method for sugar-free seedling culture. BACKGROUND

[0002] In the field of large-scale plant seedling cultivation, traditional sugar culture mode is prone to become a nutrient medium for microorganisms due to its dependence on exogenous sugar substances, resulting in a high seedling contamination rate, which seriously restricts the cultivation efficiency and quality. To break through this limitation, sugar-free culture mode has gradually become a research hotspot. The core of the sugar-free culture mode is to regulate the carbon dioxide concentration in the environment, so that the seedlings can convert carbon dioxide into sugar substances needed for their growth through photosynthesis, and use carbon dioxide as the only carbon source to reduce the risk of microbial contamination from the source.

[0003] However, the precise management of carbon dioxide in the sugar-free culture mode puts forward very high requirements. In the actual application, the existing technology still has significant shortcomings: in the concentration monitoring link, due to the different distribution densities of seedlings in the culture space, the differences in physiological activity of different growth stages, and the continuous changes in environmental factors such as temperature, humidity and light, the monitoring data is difficult to truly reflect the actual carbon source environment around the seedlings, and measurement deviation is easy to occur; in terms of concentration distribution, due to the uneven air circulation in the culture space and the local differences in seedling group respiration and photosynthesis, carbon dioxide often appears to be locally concentrated or scarce, making it difficult for some seedlings in some areas to obtain balanced carbon source supply; in terms of regulation, the existing method is difficult to dynamically adjust according to the transformation process of seedlings from heterotrophy to autotrophy and the changes in carbon demand at different growth stages, often leading to a mismatch between carbon source supply and real-time demand of seedlings, either insufficient supply limiting photosynthetic efficiency, or excessive supply causing waste and even interfering with the metabolic balance of seedlings. Therefore, in order to overcome these limitations, the present application provides a carbon dioxide monitoring system and regulation method for sugar-free seedling culture. SUMMARY

[0004] In view of the deficiencies of the prior art, the present application aims to provide a carbon dioxide monitoring system and regulation method for sugar-free seedling culture, which solves the problems of concentration monitoring deviation and uneven distribution caused by seedling distribution, growth stage and environmental factors when using carbon dioxide as a sugar source, and the inability to dynamically match the real-time carbon demand of seedlings.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0006] The carbon dioxide monitoring system for sugar-free seedling culture comprises:

[0007] The distributed grid nodes collect monitoring data in the greenhouse space, including carbon dioxide concentration and environmental parameters;

[0008] Based on the carbon dioxide concentration of the grid nodes, it is determined whether the carbon dioxide concentration distribution in the greenhouse space is potentially uneven. If so, a carbon dioxide concentration field of the greenhouse space is constructed by hierarchical interpolation based on the carbon dioxide concentration. The carbon dioxide concentration field is used to identify abnormal connected regions through connectivity analysis and dual discriminant indicators, and to solve for the target angle of the ventilation opening and the target speed of the fan in the abnormal connected regions.

[0009] By constructing a seedling environmental demand model library, the target seedling carbon dioxide demand parameters and environmental coordination regulation rules are configured. The environmental coordination regulation rules are used to correct the carbon dioxide concentration range and locate the target carbon dioxide concentration based on the carbon dioxide demand parameters and environmental parameters.

[0010] Based on the concentration deviation value in the greenhouse space, combined with the space coefficient and ventilation coefficient of the greenhouse space, the adjustment direction and adjustment range of the carbon dioxide supply rate of the carbon dioxide supply unit are updated, and anomaly monitoring and optimization feedback are carried out.

[0011] Specifically, the steps for constructing a carbon dioxide concentration field in a greenhouse space include:

[0012] Real-time carbon dioxide concentration data is acquired, and a sliding window filter is used to eliminate random noise;

[0013] Configure a deviation threshold, calculate the absolute deviation of carbon dioxide concentration between adjacent grid nodes in the greenhouse space, and count the number of sampling points of grid nodes whose absolute deviation is greater than the deviation threshold. If the absolute deviation is greater than the preset distribution anomaly threshold, the distribution state of carbon dioxide concentration in the greenhouse space is determined to be potentially uneven; otherwise, it is determined to be uniformly distributed.

[0014] When the carbon dioxide concentration distribution in the greenhouse space is determined to be potentially uneven, the spatial location of the distributed grid node in the greenhouse space is obtained.

[0015] Calculate the spatial distance between the point to be interpolated and all known grid nodes, and assign weights according to the inverse power function relationship of the distance;

[0016] By combining the three-dimensional spatial coordinate system of the greenhouse space, the interpolation dimensions are refined, and the levels and regions of the greenhouse space are divided; special areas of the greenhouse space are identified and eliminated.

[0017] The carbon dioxide concentration of each grid node at each level is interpolated in layers according to the weight of the interpolation point, and the interpolation point between levels is interpolated by calculating the concentration gradient in the vertical direction between levels.

[0018] Specifically, the steps for correcting the carbon dioxide concentration range and locating the target carbon dioxide concentration include:

[0019] A seedling environmental demand model library is constructed using a three-dimensional structured architecture of variety, growth stage, and environmental factors, storing basic biological parameters, carbon source demand parameters, and environmental synergy thresholds of the target seedlings.

[0020] Basic biological parameters include photosynthetic compensation point, photosynthetic saturation point, and carbon use efficiency curve;

[0021] Carbon source requirement parameters include the carbon dioxide concentration range and concentration fluctuation tolerance range at each growth stage of the seedlings.

[0022] Environmental collaboration thresholds are used to define the interaction parameters of environmental parameters;

[0023] Based on the variety and growth stage of the target seedlings, the basic carbon dioxide concentration range for the corresponding growth stage is retrieved from the seedling environmental demand model library.

[0024] Based on the current air temperature and humidity, the basic carbon dioxide concentration range is adjusted according to the temperature and humidity coordination rule of the environmental coordination regulation rule.

[0025] Based on real-time light intensity, the target carbon dioxide concentration is located within the corrected carbon dioxide concentration range according to the light coordination rule of the environmental coordination regulation rule.

[0026] Calculate the deviation between the target carbon dioxide concentration and the baseline carbon dioxide concentration range for the current growth stage in the seedling environmental demand model library. If the deviation exceeds the preset deviation threshold, trigger an abnormal concentration warning.

[0027] Specifically, the environmental synergistic regulation rules include temperature and humidity synergistic rules and light synergistic rules;

[0028] Temperature and humidity coordination rules are used to adjust the target carbon dioxide concentration range of the target seedling at its current growth stage based on the target seedling's current carbon dioxide concentration range, including:

[0029] Based on the seedling environmental demand model library, the temperature and humidity range of the target seedling at the current growth stage is obtained, including the photosynthetic temperature range and the transpiration humidity range.

[0030] Anomalies are detected in the air temperature and humidity of the greenhouse space. If anomalies are found, the absolute deviation ratio is calculated based on the degree to which the air temperature or humidity exceeds the corresponding temperature and humidity range. This includes the absolute deviation ratio of temperature and the absolute deviation ratio of humidity.

[0031] Select the target deviation ratio based on the absolute deviation ratio, and adjust the upper and lower limits of the carbon dioxide concentration range of the current growth stage of the target seedling downwards according to the target deviation ratio, thereby correcting the carbon dioxide concentration range of the current growth stage of the target seedling.

[0032] Specifically, the light-coordination rule is used to dynamically match the target carbon dioxide concentration based on the carbon dioxide concentration range corrected for the current growth stage of the target seedling, according to the real-time light intensity:

[0033] Based on the seedling environment demand model library, the light saturation point threshold and light compensation point threshold are obtained. When the real-time light intensity is greater than the light saturation point threshold, the target carbon dioxide concentration is located to the upper limit of the corrected carbon dioxide concentration range.

[0034] When the real-time light intensity is lower than the light compensation point threshold, the target carbon dioxide concentration is adjusted to the lower limit of the corrected carbon dioxide concentration range.

[0035] When the real-time illumination intensity is between the light compensation threshold and the light saturation threshold, the target carbon dioxide concentration is adjusted linearly according to the ratio of illumination intensity to the light saturation threshold and the light compensation threshold.

[0036] Specifically, the steps for identifying abnormally connected regions and determining the target angle of the ventilation openings and the target rotational speed of the fan within these regions include:

[0037] The typical carbon dioxide concentration in the greenhouse space and each region is calculated by spatial statistical analysis. Based on spatial adjacency and the similarity of typical carbon dioxide concentration in each region, the carbon dioxide concentration field is divided into connected regions, and the geometric center, volume and typical carbon dioxide concentration of each connected region are calculated.

[0038] By calculating the standard deviation and mean of typical carbon dioxide concentrations in all connected areas within the greenhouse space, the global spatial concentration variation coefficient is obtained. If the global spatial concentration variation coefficient is greater than a preset global threshold, local anomaly analysis is triggered.

[0039] For each connected region, calculate the deviation rate between its typical carbon dioxide concentration and the typical concentration in the greenhouse space, and filter out connected regions that exceed the preset dynamic local threshold and mark them as abnormal connected regions.

[0040] Using the geometric center of the abnormal connectivity region as a reference, extending outward along the concentration gradient direction, the location where the deviation rate between the typical carbon dioxide concentration and the typical concentration in the greenhouse space is less than the dynamic local threshold is defined as the boundary of the abnormal connectivity region.

[0041] Based on the spatial layout parameters of ventilation openings and fans in the greenhouse space, a coupled physical model of airflow concentration is constructed. Optimization objectives are set according to the deviation rate of abnormally connected areas and the total energy consumption of the equipment. A dual-objective optimization model is constructed, with decision variables including fan speed and ventilation opening angle. Constraints include fan operating power being less than rated power. The dual-objective optimization model is solved to obtain the target angle of the ventilation openings and the target speed of the fans in the greenhouse space.

[0042] Specifically, the steps for updating the direction and magnitude of the carbon dioxide replenishment unit's supply rate adjustment include:

[0043] Obtain the target carbon dioxide concentration and typical carbon dioxide concentration in the greenhouse space, calculate the concentration deviation value, and obtain the fan speed, vent angle, greenhouse space volume and vent opening area.

[0044] Based on the collected greenhouse space volume and the preset standard greenhouse space volume, the space coefficient is calculated according to the ratio between the actual greenhouse space volume and the standard greenhouse space volume.

[0045] The ventilation coefficient is calculated based on the ratio between the total opening area of ​​the ventilation vents and the surface area of ​​the greenhouse space.

[0046] Obtain the current supply rate of the greenhouse space carbon dioxide resupply unit and use it as the baseline rate;

[0047] The direction of adjustment is determined based on the sign of the concentration deviation value. When the concentration deviation value is positive, the adjustment direction is to increase the supply rate; when the concentration deviation value is negative, the adjustment direction is to decrease the supply rate.

[0048] Specifically, the steps for updating the direction and magnitude of the carbon dioxide replenishment unit's supply rate also include:

[0049] Retrieve the concentration fluctuation tolerance range of the target seedling at its current growth stage, calculate the proportion of the concentration deviation value to the width of the concentration fluctuation tolerance range, and use it as the basic adjustment ratio.

[0050] Establish spatial mapping rules and ventilation mapping rules. Spatial mapping rules are used to establish the correspondence between spatial coefficients and spatial correction gradients; ventilation mapping rules establish the correspondence between ventilation coefficients and ventilation correction factors.

[0051] Based on spatial mapping rules and ventilation mapping rules, spatial correction gradient and ventilation correction factor are obtained, and the basic adjustment ratio is weighted and corrected as the target adjustment ratio.

[0052] Multiply the target adjustment ratio by the current base rate of the carbon dioxide replenishment unit to obtain the adjustment range of the supply rate;

[0053] The constraint value is set according to the rated power of the carbon dioxide supply unit to set the constraint conditions. If the adjustment range exceeds the constraint condition range, the adjustment range is corrected according to the most recent constraint value.

[0054] Specifically, the steps for anomaly monitoring and optimization feedback include:

[0055] Once the supply rate adjustment direction and magnitude of the carbon dioxide replenishment unit are updated and issued, dynamic tracking of the concentration field is initiated to obtain the carbon dioxide distribution status in the greenhouse space and the typical carbon dioxide concentration in the greenhouse space.

[0056] Calculate the concentration deviation value and statistically analyze the duration of the concentration deviation control.

[0057] Configure a concentration deviation threshold. When the concentration deviation value is greater than the concentration deviation threshold, enter the timeliness judgment process to determine whether the duration of the concentration deviation control is greater than the preset control threshold. If so, trigger an abnormal warning and trigger an update according to the logic of first equalizing and then adjusting the supply.

[0058] When the concentration deviation is less than or equal to the concentration deviation threshold, it is determined that the current regulation has brought the concentration deviation back to a reasonable range, and the current supply rate of the carbon dioxide replenishment unit is maintained.

[0059] Methods for controlling carbon dioxide levels in sugar-free seedling culture include:

[0060] Step S1: Collect monitoring data within the greenhouse space through distributed grid nodes. The monitoring data includes carbon dioxide concentration and environmental parameters.

[0061] Step S2: Based on the carbon dioxide concentration of the grid nodes, determine whether the carbon dioxide concentration distribution in the greenhouse space is potentially uneven. If so, construct the carbon dioxide concentration field of the greenhouse space through hierarchical interpolation based on the carbon dioxide concentration. The carbon dioxide concentration field is used to identify abnormal connected regions through connectivity analysis and dual discriminant indicators, and to solve for the target angle of the ventilation opening and the target speed of the fan in the abnormal connected regions.

[0062] Step S3: By constructing a seedling environmental demand model library, configure the target seedling carbon dioxide demand parameters and environmental coordination rules. The environmental coordination rules are used to correct the carbon dioxide concentration range and locate the target carbon dioxide concentration based on the carbon dioxide demand parameters and environmental parameters.

[0063] Step S4: Based on the concentration deviation value of the greenhouse space, combined with the space coefficient and ventilation coefficient of the greenhouse space, update the adjustment direction and adjustment range of the carbon dioxide supply rate of the carbon dioxide supply unit.

[0064] Step S5: Monitor and optimize the supply rate of the carbon dioxide replenishment unit.

[0065] The beneficial effects of this invention are:

[0066] This invention constructs a carbon dioxide concentration field through distributed grid acquisition and hierarchical interpolation. Combined with connectivity analysis and dual discriminant indicators, it accurately identifies abnormal areas and optimizes ventilation parameters, effectively solving the problem of uneven carbon dioxide concentration distribution in sugar-free seedling cultivation. This ensures the uniformity of the concentration field in the greenhouse space and prevents excessively high or low concentrations from affecting seedling growth. By constructing a seedling environmental demand model library and environmental collaborative adjustment rules, it achieves dynamic correction and precise positioning of the target carbon dioxide concentration, solving the problem of poor dynamic adaptability between supply and demand, and ensuring that the concentration supply matches the physiological needs of seedlings at different growth stages. By adjusting the replenishment rate with spatial and ventilation coefficients and conducting anomaly monitoring and feedback, it further improves the accuracy of the adaptation between supply and spatial scale and ventilation capacity, forming a closed loop of distribution optimization, demand matching, and replenishment regulation. This significantly improves the intelligence and precision of carbon dioxide regulation in sugar-free seedling cultivation, ensuring a stable seedling growth environment. Attached Figure Description

[0067] Figure 1 This is a schematic diagram of the carbon dioxide monitoring system for sugar-free seedling cultivation according to the present invention;

[0068] Figure 2 A flowchart for constructing a carbon dioxide concentration field in a greenhouse space for this invention;

[0069] Figure 3 This is a flowchart illustrating the process of identifying abnormal connected regions in this invention;

[0070] Figure 4 A flowchart illustrating the adjustment direction and magnitude of the carbon dioxide replenishment unit supply rate in this invention;

[0071] Figure 5 This is a flowchart of the carbon dioxide regulation method for sugar-free seedling culture according to the present invention. Detailed Implementation

[0072] Please see Figure 1 This embodiment introduces a carbon dioxide monitoring system for sugar-free seedling cultivation, including an environmental sensing module, a concentration reconstruction module, a target concentration module, a collaborative control module, and a feedback optimization module.

[0073] The environmental sensing module is used to collect monitoring data within the greenhouse space by configuring multispectral sensing units and environmental parameter sensing units according to a preset distributed grid node configuration. This data includes carbon dioxide concentration and environmental parameters. The environmental parameters include light intensity, air temperature, air humidity, and airflow velocity.

[0074] In this embodiment, the multispectral sensing unit and the environmental parameter sensing unit adopt an integrated distributed deployment architecture, uniformly covering the target seedling cultivation area in the greenhouse space according to a preset grid, ensuring no blind spots in monitoring. Each distributed node of the multispectral sensing unit integrates a multi-band laser spectral sensor, using differential absorption spectroscopy technology to suppress background light interference and improve the stability and accuracy of carbon dioxide concentration measurement. The environmental parameter sensing unit, through an integrated spectrometer, temperature and humidity sensor, and an anemometer, simultaneously acquires data such as light intensity, air temperature and humidity, and airflow speed, providing an environmental compensation benchmark for the concentration measurement of the multispectral sensing unit. Monitoring data is synchronized through a unified edge computing node, ensuring the spatiotemporal consistency of monitoring data and providing reliable basic data support for subsequent modules.

[0075] The concentration reconstruction module is used to determine the carbon dioxide concentration distribution based on the carbon dioxide concentration collected by the multispectral sensing unit, and to generate a carbon dioxide concentration field based on the distributed carbon dioxide concentration. It configures the concentration uniformity discrimination rules and the correlation analysis of airflow diffusion in the greenhouse space to identify areas of abnormal concentration and generate target angles for vents and target rotation speeds for fans that are adapted to the greenhouse space structure. This allows for accurate location of concentration accumulation areas and provides a basis for decision-making for uniform flow control.

[0076] In this embodiment, the concentration reconstruction module employs distributed data fusion and 3D modeling. Based on discrete carbon dioxide concentration data collected by multispectral sensing units, it constructs a 3D carbon dioxide concentration field in the greenhouse space through interpolation combined with fluid dynamic constraints. By defining multi-dimensional evaluation indicators such as spatial variation coefficient, local deviation index, and ventilation efficiency index, and setting early warning thresholds, it achieves dynamic evaluation of concentration uniformity. Furthermore, by establishing a greenhouse space airflow model based on computational fluid dynamics, it identifies the impact of key flow characteristics such as vortex regions and low-speed regions on concentration distribution. Based on this, a multi-objective optimization model is constructed to minimize the concentration variation coefficient, local deviation, and energy consumption, solving for the optimal control scheme including fan speed and vent angle.

[0077] Preferably, the specific steps for identifying areas of abnormal concentration and generating optimized airflow paths adapted to the greenhouse spatial structure include:

[0078] Please see Figure 2 The system acquires carbon dioxide concentration data in real time by deploying multispectral sensing units in distributed grid nodes in the greenhouse space, and uses sliding window filtering to eliminate random noise, providing high-quality raw data for subsequent analysis and ensuring the temporal continuity and stability of the data.

[0079] A deviation threshold is configured to define significant differences in carbon dioxide concentration between adjacent grid nodes. Based on the tolerance threshold of seedlings to carbon source fluctuations in sugar-free culture, the absolute deviation of carbon dioxide concentration between adjacent grid nodes in the greenhouse space is calculated. The number of sampling points of grid nodes with absolute deviations greater than the deviation threshold is counted. If the number exceeds the preset distribution anomaly threshold, the carbon dioxide concentration distribution in the greenhouse space is determined to be potentially uneven; otherwise, it is determined to be uniformly distributed. The distribution anomaly threshold is used to distinguish the duration of local minor fluctuations and is set based on the total number of grids in the greenhouse space and the seedling distribution density. Based on the concentration deviation and duration between adjacent nodes, potential uneven distribution states can be quickly screened, avoiding complex subsequent analyses triggered by local minor fluctuations, reducing invalid calculations, and improving response efficiency.

[0080] When the carbon dioxide concentration distribution within the greenhouse space is determined to be potentially uneven, a carbon dioxide concentration field is constructed based on discrete carbon dioxide concentration data. This upgrades the carbon dioxide concentration distribution from point data to spatial volume data, providing a continuous field basis for subsequent regional division.

[0081] The spatial location of the distributed grid nodes in the greenhouse space is obtained. For any point to be interpolated, its spatial distance to all known grid nodes is calculated. Weights are assigned according to the inverse power function relationship of the distance. The power exponent is dynamically adjusted according to the structural characteristics of the greenhouse space to ensure that the influence of the nearest neighbor nodes on the interpolation results is dominant. For the special case where the distance is zero, that is, the point to be interpolated coincides with a known node, the maximum weight value is directly assigned, and the weights of the other nodes are normalized.

[0082] Furthermore, by combining the three-dimensional spatial coordinate system of the greenhouse space, the interpolation dimension is refined, and the greenhouse space is divided into multiple levels and regions according to the three-dimensional coordinate system. Special regions of the greenhouse space are defined, including boundary regions, ventilation opening regions, and fan regions, while special regions with special carbon dioxide concentration fields in the greenhouse space are eliminated.

[0083] Carbon dioxide concentration data of grid nodes at different height levels are interpolated in layers according to the weight of the interpolation points. Taking into account the height of the seedling canopy and the vertical distribution characteristics of airflow, the concentration gradient in the vertical direction between layers is calculated to interpolate the interpolation points between layers, smoothly transitioning the carbon dioxide concentration data of the same height level, so as to finally construct the carbon dioxide concentration field of the greenhouse space. Through three-dimensional layer division and vertical gradient smoothing, the neglect of vertical concentration differences in the basic interpolation is made up for, and the spatial precision of the interpolation is improved by combining the characteristics of the seedling canopy and airflow. Special areas such as boundaries and vents are eliminated to reduce the pollution of the concentration field by non-uniform interference.

[0084] Please see Figure 3This study calculates typical carbon dioxide concentrations in greenhouse spaces and for each region through spatial statistical analysis. Connectivity analysis is performed on continuous regions of carbon dioxide concentration. Based on spatial adjacency and the similarity of typical carbon dioxide concentrations in each region, the carbon dioxide concentration field is divided into multiple connected regions. For each connected region, its geometric center, volume, and typical carbon dioxide concentration are calculated. The typical carbon dioxide concentration is a weighted average of the carbon dioxide concentrations within the region, with the weights dynamically adjusted based on the distance from grid points to the region center. This transformation of the continuous concentration field into discrete connected regions converts the concentration distribution from a disordered continuous field into ordered regional units, providing calculable regional-level parameters for anomaly analysis.

[0085] Anomaly screening is performed on each connected region using both global and local discriminant indicators. First, the standard deviation and mean of typical carbon dioxide concentrations in all connected regions within the greenhouse space are calculated to obtain the global spatial concentration variation coefficient. If the global spatial concentration variation coefficient exceeds a preset global threshold, local anomaly analysis is triggered. For each connected region, the deviation rate between its typical carbon dioxide concentration and the typical concentration in the greenhouse space is calculated. Connected regions exceeding a preset dynamic local threshold are marked as abnormal connected regions. The global threshold is set based on the carbon source stability requirements of the seedling growth stage; for example, a lower variation coefficient is needed during vigorous growth to ensure a stable carbon source supply. The dynamic local threshold is set according to the characteristics of the target seedlings within the connected region. In densely populated seedling areas, due to higher carbon source utilization efficiency and more stable demand, the threshold is set to a stricter level, while the threshold is appropriately relaxed in sparse areas or seedling areas to ensure that anomaly detection matches the actual physiological needs of the seedlings. If the global spatial concentration variation coefficient is less than or equal to the preset global threshold, the typical carbon dioxide concentration in the greenhouse space is calculated through spatial statistical analysis based on the carbon dioxide concentration between grid nodes.

[0086] Using the geometric center of the abnormal connectivity region as a reference, extending outward along the concentration gradient direction, the location where the deviation rate between the typical carbon dioxide concentration and the typical concentration in the greenhouse space is less than the dynamic local threshold is defined as the boundary of the abnormal connectivity region.

[0087] Based on the spatial layout parameters of ventilation openings and fans in the greenhouse space, including location coordinates, quantity, rated wind speed, and adjustable angle range, a coupled physical model of airflow concentration is constructed: the boundary of the abnormally connected area is used as the key constraint input, and the airflow field distribution under different combinations of fan speed and ventilation opening angle is simulated using computational fluid dynamics methods. The rate and path of carbon dioxide diffusion driven by airflow are calculated, and the mapping relationship between control parameters and the degree of improvement in concentration distribution is established.

[0088] Based on the airflow concentration coupled physical model, optimization objectives are set according to the deviation rate of abnormal connected areas and the total energy consumption of equipment. For example, the dual-objective optimization model is set with the deviation rate of abnormal connected areas being less than the dynamic local threshold and the total energy consumption of equipment being minimized. The fan speed and the vent angle are set as decision variables, and the constraint is that the fan operating power is less than the rated power. The dual-objective optimization model is solved by a genetic algorithm to obtain the target vent angle and the target fan speed in the greenhouse space.

[0089] When the carbon dioxide concentration distribution in the greenhouse space is determined to be uniform, the typical carbon dioxide concentration in the greenhouse space is calculated through spatial statistical analysis based on the carbon dioxide concentration between grid nodes.

[0090] The target concentration module is used to generate target carbon dioxide concentrations that are adapted to the growth needs of target seedlings. By building an extensible seedling environment demand model library, it configures the carbon dioxide demand parameters and environmental coordination rules for target seedlings of different varieties and growth stages. This enables dynamic correction of the target carbon dioxide concentration by combining real-time environmental parameters such as light and humidity with the growth characteristics of the seedling population, so as to ensure that the target carbon dioxide concentration is accurately matched with the real-time growth needs of the target seedlings.

[0091] In this embodiment, the target concentration module achieves precise generation of dynamic target concentrations by constructing a multi-level target seedling environmental demand model library. Preferably, a three-dimensional structured architecture of variety, growth stage, and environmental factors is used to construct the seedling environmental demand model library, storing basic biological parameters, carbon source demand parameters, and environmental synergy thresholds for the target seedlings. By accurately matching variety, growth stage, and environmental parameters, the retrieved basic data is ensured to be targeted, providing a benchmark for variety-specific and stage-adaptive concentration adjustments, avoiding adaptation deviations caused by general parameters. The basic biological parameters include the photosynthetic compensation point, photosynthetic saturation point, and carbon utilization efficiency curves for different seedling varieties; the carbon source demand parameters cover the carbon dioxide concentration range, concentration fluctuation tolerance range, and minimum carbon dioxide replenishment rate for each growth stage, including germination, seedling, vigorous growth, and maturity; the environmental synergy thresholds define the interaction parameters between light intensity, air temperature, air humidity, and carbon dioxide concentration. The interaction coefficients are set and stored according to variety and growth stage, including photosynthetic temperature range, transpiration humidity range, light saturation point threshold, light compensation point threshold, and concentration deviation threshold system.

[0092] Preferably, the environmental synergistic regulation rules are formulated based on the photosynthetic mechanism and the physiological characteristics of seedlings. Specifically, the environmental synergistic regulation rules include temperature and humidity synergistic rules and light synergistic rules:

[0093] Existing technologies often use fixed concentration ranges, failing to consider the impact of temperature and humidity on seedling carbon utilization. For example, maintaining high concentrations at high temperatures leads to carbon source waste, while high concentrations at low humidity cannot be effectively absorbed. The temperature and humidity synergy rule is used to adjust the target carbon dioxide concentration range based on the current growth stage of the target seedling, maintaining a balance between photosynthetic efficiency and carbon source utilization.

[0094] Based on the seedling environmental demand model library, the photosynthetic temperature range and transpiration humidity range of the target seedling at the current growth stage are obtained;

[0095] Anomalies are detected in the air temperature and humidity of the greenhouse space. If the current air temperature is outside the photosynthetic temperature range or the current air humidity is outside the transpiration humidity range, the current greenhouse space is determined to be abnormal. The absolute deviation ratio is calculated according to the degree to which the air temperature exceeds the photosynthetic temperature range or the degree to which the air humidity exceeds the transpiration humidity range, including the absolute deviation ratio of temperature and the absolute deviation ratio of humidity.

[0096] The maximum absolute deviation ratio is selected as the target deviation ratio. Based on the target deviation ratio, the upper and lower limits of the carbon dioxide concentration range for the current growth stage of the target seedlings are adjusted downwards to correct the carbon dioxide concentration range for the current growth stage of the target seedlings. The basic concentration range is dynamically corrected by adjusting the temperature and humidity to adapt the range to the photosynthetic physiological state under abnormal temperature and humidity conditions. For example, the concentration range is reduced when high temperature inhibits photosynthetic enzyme activity, and the range is contracted when stomata close due to low humidity, thus avoiding the imbalance between carbon source supply and photosynthetic efficiency caused by temperature and humidity fluctuations.

[0097] In traditional light regulation, light intensity and carbon dioxide concentration are often controlled independently without establishing a correlation. For example, insufficient concentration under strong light limits photosynthesis, while excessively high concentration under weak light leads to waste and low photosynthetic efficiency. The light-coordination rule uses a carbon dioxide concentration range corrected for the current growth stage of the target seedling to dynamically match the target carbon dioxide concentration according to real-time light intensity, thus adapting to the photosynthetic needs of the target seedling at its current growth stage.

[0098] Based on a seedling environmental demand model library, light saturation and light compensation thresholds are obtained. When the real-time light intensity exceeds the light saturation threshold, the target carbon dioxide concentration is set to the upper limit of the corrected carbon dioxide concentration range. When the real-time light intensity is below the light compensation threshold, the target carbon dioxide concentration is set to the lower limit of the corrected carbon dioxide concentration range. When the real-time light intensity is between the light compensation and light saturation thresholds, the target carbon dioxide concentration is linearly adjusted according to the ratio of light intensity to the light saturation and light compensation thresholds, with the ratio coefficient configured according to the target seedling variety and growth stage. Within the corrected range, the target concentration is precisely located based on the real-time light intensity, dynamically matching carbon source supply with photosynthetic intensity. High concentrations under strong light satisfy high photosynthetic rates, while low concentrations under weak light avoid carbon source waste and improve carbon utilization efficiency.

[0099] Preferably, the specific steps for generating a target carbon dioxide concentration that is suitable for the growth requirements of the target seedlings include:

[0100] The target seedling's variety and growth stage are obtained, along with the current air temperature, air humidity, and real-time light intensity uploaded by the environmental sensing module. Based on the target seedling's variety and growth stage, the basic carbon dioxide concentration range, photosynthetic temperature range, transpiration humidity range, light saturation point threshold, light compensation point threshold, and proportional coefficient for the corresponding growth stage are retrieved from the seedling environmental demand model library.

[0101] Based on the current air temperature and humidity, the basic carbon dioxide concentration range is corrected according to the temperature and humidity coordination rule; based on the real-time light intensity, the target carbon dioxide concentration is located within the corrected carbon dioxide concentration range according to the light intensity coordination rule.

[0102] The system calculates the deviation between the target carbon dioxide concentration and the baseline carbon dioxide concentration range for the current growth stage in the seedling environmental demand model library. If this deviation exceeds a preset deviation threshold, an anomaly warning is triggered, indicating that the target carbon dioxide concentration may not match the actual growth state of the seedlings, requiring further optimization of the parameters in the environmental coordination regulation rules based on growth characteristics. The deviation threshold defines the acceptable fluctuation boundary of the target carbon dioxide concentration relative to the baseline range, distinguishing between normal deviations caused by environmental regulation and abnormal deviations that may affect seedling physiological metabolism. This avoids triggering invalid warnings due to oversensitivity or overlooking potential risks due to an overly broad threshold. By monitoring the deviation between the target concentration and the baseline range, abnormal concentrations caused by environmental fluctuations or parameter deviations can be identified in a timely manner, preventing abnormal states from continuously affecting seedling growth and providing trigger signals for parameter optimization.

[0103] The collaborative control module is used to coordinate and regulate the operating status of the carbon dioxide supply unit based on the target carbon dioxide concentration generated by the target concentration module and the typical carbon dioxide concentration of the greenhouse space output by the concentration reconstruction module, combined with the target fan speed and target vent angle determined by the concentration reconstruction module. It updates the adjustment direction and adjustment range of the carbon dioxide supply rate of the carbon dioxide supply unit, generates control commands for the carbon dioxide supply unit, and achieves precise coordination between carbon source supply and airflow diffusion, ensuring that the carbon dioxide concentration in the greenhouse space quickly approaches and stabilizes within the target carbon dioxide concentration range.

[0104] Please see Figure 4 Preferably, the specific steps for updating the adjustment direction and adjustment range of the carbon dioxide supply rate of the carbon dioxide supply unit and generating control commands for the carbon dioxide supply unit include:

[0105] The system acquires in real time the target carbon dioxide concentration generated by the target concentration module, the typical carbon dioxide concentration of the greenhouse space output by the concentration reconstruction module, and the current fan speed and vent angle in the greenhouse space; it also acquires the volume of the greenhouse space and the opening area of ​​the vents, providing reliable input for subsequent analysis.

[0106] Based on the collected greenhouse space volume and the preset standard greenhouse space volume, a space coefficient is calculated according to the ratio of the actual greenhouse space volume to the standard greenhouse space volume; based on the total opening area of ​​the ventilation vents and the surface area of ​​the greenhouse space, a ventilation coefficient is calculated according to the ratio of the total opening area of ​​the ventilation vents to the surface area of ​​the greenhouse space. The standard greenhouse space volume is used as a benchmark to measure the actual greenhouse space size, unifying the calculation dimension of the replenishment strategy for greenhouse spaces of different sizes, and avoiding incomparability of control parameters due to volume differences.

[0107] The concentration deviation value is calculated by combining the target carbon dioxide concentration with the current typical carbon dioxide concentration in the greenhouse space. When the concentration deviation value is positive, it indicates that the typical carbon dioxide concentration in the greenhouse space is lower than the target carbon dioxide concentration, and the supply intensity of the carbon dioxide supply unit needs to be activated or increased. When the concentration deviation value is negative, it indicates that the typical carbon dioxide concentration in the greenhouse space is higher than the target carbon dioxide concentration, and the supply of the carbon dioxide supply unit needs to be reduced or stopped, and the control should be combined with the fans and vents.

[0108] Obtain the current carbon dioxide supply rate of the greenhouse space carbon dioxide refueling unit, use it as a baseline rate, and update the adjustment direction and magnitude of the carbon dioxide refueling unit supply rate by combining the concentration deviation value, space coefficient, and ventilation coefficient:

[0109] The direction of adjustment is determined based on the sign of the concentration deviation value. When the concentration deviation value is positive, the adjustment direction is to increase the supply rate; when the concentration deviation value is negative, the adjustment direction is to decrease the supply rate.

[0110] Retrieve the concentration fluctuation tolerance range of the target seedling at its current growth stage. The concentration fluctuation tolerance range is stored in the seedling environmental demand model library. Calculate the proportion of the concentration deviation value to the width of the concentration fluctuation tolerance range as the basic adjustment ratio.

[0111] The basic adjustment ratio is amplified based on the spatial coefficient, and the corrected ratio is further corrected based on the ventilation coefficient. Spatial mapping rules and ventilation mapping rules are established separately. The spatial mapping rules are used to establish the correspondence between the spatial coefficient and the spatial correction gradient, ensuring that the adjustment range is accurately matched with the greenhouse space volume. This is established by configuring a preset spatial coefficient and correction gradient mapping table, which is stored in the parameter configuration library of the collaborative control module. The table presets a unique spatial correction gradient according to the continuous gradient of the spatial coefficient. The gradient value increases stepwise as the spatial coefficient increases, covering both conventional and extreme greenhouse space volume scenarios. The ventilation mapping rules establish the correspondence between the ventilation coefficient and the ventilation correction multiple, ensuring that the adjustment range is dynamically matched with the airflow diffusion capacity. This is established by configuring a preset ventilation coefficient and correction multiple mapping table, which is stored in the parameter configuration library. The table presets a unique ventilation correction multiple according to the continuous gradient of the ventilation coefficient. The multiple increases stepwise as the ventilation coefficient increases, adapting to the airflow exchange capacity under different ventilation openings.

[0112] Based on the space coefficient and ventilation coefficient of the greenhouse space, the space correction gradient and ventilation correction factor are obtained based on the space mapping rule and ventilation mapping rule. The basic adjustment ratio is then weighted and corrected as the target adjustment ratio.

[0113] The target adjustment ratio is multiplied by the current baseline rate of the carbon dioxide replenishment unit to obtain the adjustment range of the supply rate. At the same time, constraint values ​​are set according to the rated power of the carbon dioxide replenishment unit to set constraint conditions. The constraint values ​​include: the rated maximum supply rate and the minimum carbon dioxide concentration replenishment rate. The constraint conditions include: the target speed must not exceed the rated maximum supply rate of the carbon dioxide replenishment unit to avoid equipment overload, and must not be lower than the minimum carbon dioxide concentration replenishment rate required for the basal metabolism of the target seedling at the current growth stage. This is stored in the carbon source demand parameters of the seedling environmental demand model library to ensure that the seedling respiration and basal growth needs are met. If the adjustment range exceeds the range of constraint conditions, the adjustment range is corrected according to the most recent constraint value.

[0114] The direction and magnitude of the carbon dioxide supply rate adjustment are linked to the commands for the target fan speed and the target vent angle, and sent to the execution end at the same timestamp to regulate the carbon dioxide concentration and distribution in the greenhouse space.

[0115] The feedback optimization module is used to update the carbon dioxide concentration distribution and typical carbon dioxide concentration in the greenhouse space based on the detection data collected in real time by the environmental sensing module. It also locates the target carbon dioxide concentration based on the detection data, dynamically triggers the update of the control commands of the carbon dioxide supply unit, performs anomaly monitoring and optimization feedback, and forms a closed-loop optimization mechanism for the entire chain.

[0116] Preferably, the specific steps for dynamically triggering the update of the carbon dioxide replenishment unit control commands, and for anomaly monitoring and optimization feedback include:

[0117] After the carbon dioxide supply rate of the carbon dioxide supply unit is adjusted, there are spatiotemporal differences in the diffusion of carbon dioxide in the greenhouse space. When the adjustment direction and magnitude of the carbon dioxide supply rate of the carbon dioxide supply unit are updated and issued, the concentration field dynamic tracking is initiated. The carbon dioxide distribution status in the greenhouse space and the typical carbon dioxide concentration in the greenhouse space are obtained through the concentration reconstruction module, providing comprehensive and accurate basic data for subsequent deviation analysis and control optimization.

[0118] The concentration deviation value directly reflects the difference between the current concentration and the target, while the duration of the deviation can determine whether the control measures are effective. The typical carbon dioxide concentration in the greenhouse space is continuously compared with the target carbon dioxide concentration, the concentration deviation value is calculated, and the duration of the deviation control is statistically analyzed, which is the cumulative time from the effective date of the replenishment rate adjustment command to the present.

[0119] Configure a concentration deviation threshold, which is set based on the concentration fluctuation tolerance range of the target seedling at the current growth stage. For example, take 30% of the tolerance range width and store it in the seedling environment demand model library to define the degree of concentration deviation that needs to be focused on intervention.

[0120] If the concentration deviation exceeds the limit and the duration is short, it may recover naturally through existing control. If the deviation continues for an extended period, it indicates a defect in the current control scheme. When the concentration deviation value exceeds the concentration deviation threshold, the timeliness judgment process is initiated to determine whether the duration of the concentration deviation control exceeds the preset control threshold. If so, an abnormal warning is triggered, indicating that the concentration deviation exceeds the limit and the timeout is prolonged, indicating insufficient control efficiency. At this point, an update is triggered according to the logic of first equalizing the flow and then adjusting the supply.

[0121] The distribution status adjustment mechanism is activated, and the concentration reconstruction module is invoked to adjust the target angle of the ventilation openings and the target speed of the fans to accelerate the spatial diffusion of carbon dioxide. The distribution status is monitored in real time. When the concentration reconstruction module determines that the distribution status of the greenhouse space is uniform, the typical carbon dioxide concentration of the greenhouse space at this time is recalculated. Based on the deviation between the new typical carbon dioxide concentration and the target concentration, the supply rate adjustment direction and amplitude of the carbon dioxide supply unit are updated through the collaborative control module, and new control commands are generated.

[0122] If the duration of the concentration deviation control is less than or equal to the preset control threshold, continue to monitor the greenhouse space concentration deviation threshold. If the deviation exceeds the standard but the duration does not exceed the time limit, it may be that the control measures have not yet taken full effect. In this case, continue to monitor to avoid frequent adjustments that could cause system oscillations.

[0123] When the concentration deviation is less than or equal to the concentration deviation threshold, it is determined that the current control has brought the concentration deviation back to a reasonable range. The supply rate of the current carbon dioxide supply unit is maintained, and the typical carbon dioxide concentration in the greenhouse space is continuously monitored. After the concentration deviation returns to a reasonable range, blind adjustments may lead to new deviations; however, continuous monitoring can promptly detect trends of concentration deviation again, ensuring stability within the target range. At the same time, continuous monitoring prevents deviation rebounds and ensures the stability of the seedling growth environment.

[0124] Please see Figure 5 This embodiment describes a method for regulating carbon dioxide in sugar-free seedling culture, including:

[0125] Step S1: Collect monitoring data within the greenhouse space through distributed grid nodes. The monitoring data includes carbon dioxide concentration and environmental parameters.

[0126] Step S2: Based on the carbon dioxide concentration of the grid nodes, determine whether the carbon dioxide concentration distribution in the greenhouse space is potentially uneven. If so, construct the carbon dioxide concentration field of the greenhouse space through hierarchical interpolation based on the carbon dioxide concentration. The carbon dioxide concentration field is used to identify abnormal connected regions through connectivity analysis and dual discriminant indicators, and to solve for the target angle of the ventilation opening and the target speed of the fan in the abnormal connected regions.

[0127] Step S3: By constructing a seedling environmental demand model library, configure the target seedling carbon dioxide demand parameters and environmental coordination rules. The environmental coordination rules are used to correct the carbon dioxide concentration range and locate the target carbon dioxide concentration based on the carbon dioxide demand parameters and environmental parameters.

[0128] Step S4: Based on the concentration deviation value of the greenhouse space, combined with the space coefficient and ventilation coefficient of the greenhouse space, update the adjustment direction and adjustment range of the carbon dioxide supply rate of the carbon dioxide supply unit.

[0129] Step S5: Monitor and optimize the supply rate of the carbon dioxide replenishment unit.

[0130] Preferably, the specific steps for constructing a carbon dioxide concentration field in a greenhouse space include:

[0131] Real-time carbon dioxide concentration data is acquired, and a sliding window filter is used to eliminate random noise;

[0132] Configure a deviation threshold, calculate the absolute deviation of carbon dioxide concentration between adjacent grid nodes in the greenhouse space, and count the number of sampling points of grid nodes whose absolute deviation is greater than the deviation threshold. If the absolute deviation is greater than the preset distribution anomaly threshold, the distribution state of carbon dioxide concentration in the greenhouse space is determined to be potentially uneven; otherwise, it is determined to be uniformly distributed.

[0133] When the carbon dioxide concentration distribution in the greenhouse space is determined to be potentially uneven, the spatial location of the distributed grid node in the greenhouse space is obtained.

[0134] Calculate the spatial distance between the point to be interpolated and all known grid nodes, and assign weights according to the inverse power function relationship of the distance;

[0135] By combining the three-dimensional spatial coordinate system of the greenhouse space, the interpolation dimensions are refined, and the levels and regions of the greenhouse space are divided; special areas of the greenhouse space are identified and eliminated.

[0136] The carbon dioxide concentration of each grid node at each level is interpolated in layers according to the weight of the interpolation point, and the interpolation point between levels is interpolated by calculating the concentration gradient in the vertical direction between levels.

[0137] Preferably, the specific steps for correcting the carbon dioxide concentration range and locating the target carbon dioxide concentration include:

[0138] A seedling environmental demand model library is constructed using a three-dimensional structured architecture of variety, growth stage, and environmental factors, storing basic biological parameters, carbon source demand parameters, and environmental synergy thresholds of the target seedlings.

[0139] Basic biological parameters include photosynthetic compensation point, photosynthetic saturation point, and carbon use efficiency curve;

[0140] Carbon source requirement parameters include the carbon dioxide concentration range and concentration fluctuation tolerance range at each growth stage of the seedlings.

[0141] Environmental collaboration thresholds are used to define the interaction parameters of environmental parameters;

[0142] Based on the variety and growth stage of the target seedlings, the basic carbon dioxide concentration range for the corresponding growth stage is retrieved from the seedling environmental demand model library.

[0143] Based on the current air temperature and humidity, the basic carbon dioxide concentration range is adjusted according to the temperature and humidity coordination rule of the environmental coordination regulation rule.

[0144] Based on real-time light intensity, the target carbon dioxide concentration is located within the corrected carbon dioxide concentration range according to the light coordination rule of the environmental coordination regulation rule.

[0145] Calculate the deviation between the target carbon dioxide concentration and the baseline carbon dioxide concentration range for the current growth stage in the seedling environmental demand model library. If the deviation exceeds the preset deviation threshold, trigger an abnormal concentration warning.

[0146] Preferably, the specific steps for adjusting the direction and magnitude of the carbon dioxide replenishment unit's supply rate include:

[0147] Obtain the target carbon dioxide concentration and typical carbon dioxide concentration in the greenhouse space, calculate the concentration deviation value, and obtain the fan speed, vent angle, greenhouse space volume and vent opening area.

[0148] Based on the collected greenhouse space volume and the preset standard greenhouse space volume, the space coefficient is calculated according to the ratio between the actual greenhouse space volume and the standard greenhouse space volume.

[0149] The ventilation coefficient is calculated based on the ratio between the total opening area of ​​the ventilation vents and the surface area of ​​the greenhouse space.

[0150] Obtain the current supply rate of the greenhouse space carbon dioxide resupply unit and use it as the baseline rate;

[0151] The direction of adjustment is determined based on the sign of the concentration deviation value. When the concentration deviation value is positive, the adjustment direction is to increase the supply rate; when the concentration deviation value is negative, the adjustment direction is to decrease the supply rate.

[0152] Retrieve the concentration fluctuation tolerance range of the target seedling at its current growth stage, calculate the proportion of the concentration deviation value to the width of the concentration fluctuation tolerance range, and use it as the basic adjustment ratio.

[0153] Establish spatial mapping rules and ventilation mapping rules. Spatial mapping rules are used to establish the correspondence between spatial coefficients and spatial correction gradients; ventilation mapping rules establish the correspondence between ventilation coefficients and ventilation correction factors.

[0154] Based on spatial mapping rules and ventilation mapping rules, spatial correction gradient and ventilation correction factor are obtained, and the basic adjustment ratio is weighted and corrected as the target adjustment ratio.

[0155] Multiply the target adjustment ratio by the current base rate of the carbon dioxide replenishment unit to obtain the adjustment range of the supply rate;

[0156] The constraint value is set according to the rated power of the carbon dioxide supply unit to set the constraint conditions. If the adjustment range exceeds the constraint condition range, the adjustment range is corrected according to the most recent constraint value.

[0157] Working principle and its effects:

[0158] This invention collects carbon dioxide concentration and environmental parameters within a greenhouse space through distributed grid nodes. This multi-point distributed layout overcomes the limitations of single-point monitoring, comprehensively capturing concentration differences within the space and providing a complete data foundation for subsequent analysis. By constructing a carbon dioxide concentration field using hierarchical interpolation, and combining connectivity analysis with global + local dual-discrimination indicators, abnormal connectivity areas can be accurately located. Furthermore, a dual-objective optimization model is used to solve for the ventilation opening angle and fan speed, achieving targeted treatment of uneven concentration distribution, reducing ineffective energy consumption, significantly improving the uniformity of concentration in the greenhouse space, and preventing local concentration imbalances from affecting seedling growth.

[0159] Based on a three-dimensional framework of variety, growth stage, and environmental factors, the seedling environmental demand model library stores parameters such as photosynthetic compensation point and concentration tolerance range. Combined with temperature and humidity coordination rules and light coordination rules, it can dynamically adjust the target concentration, greatly improve the matching degree between supply and seedling physiological needs, and solve the problem of the disconnect between traditional fixed concentration supply and dynamic demand.

[0160] By weighting the replenishment range using space coefficients and ventilation coefficients, and setting dual constraints on equipment rated power and seedling basic requirements, insufficient replenishment or overload can be avoided. Combined with an anomaly monitoring mechanism, a closed-loop control is formed, which significantly improves the concentration compliance rate. Ultimately, intelligent and precise control of carbon dioxide in sugar-free seedling cultivation is achieved, ensuring a stable seedling growth environment and promoting increased growth rate.

[0161] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principle of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A sugar-free seedling culture carbon dioxide monitoring system, characterized by, The method comprises the following steps: Collecting monitoring data in the greenhouse space by distributed grid nodes, the monitoring data including carbon dioxide concentration and environmental parameters; Calculating the typical carbon dioxide concentration of the greenhouse space based on the carbon dioxide concentration of the grid nodes, and determining whether the carbon dioxide concentration distribution state in the greenhouse space is potentially uneven. If so, a carbon dioxide concentration field of the greenhouse space is constructed by stratified interpolation based on the carbon dioxide concentration; the carbon dioxide concentration field is used to identify an abnormal connected region by connectivity analysis and double discrimination indicators, and to solve the target angle of the ventilation port and the target speed of the fan in the abnormal connected region; By constructing a seedling environmental demand model library, configuring target seedling carbon dioxide demand parameters and environmental collaborative regulation rules, the environmental collaborative regulation rules are used to correct the carbon dioxide concentration interval and locate the target carbon dioxide concentration according to the carbon dioxide demand parameters and the environmental parameters; According to the concentration deviation value of the greenhouse space, combining the space coefficient and the ventilation coefficient of the greenhouse space, the adjustment direction and adjustment amplitude of the carbon dioxide supply unit supply rate are updated, and abnormal monitoring and optimization feedback are performed; The specific steps of constructing the carbon dioxide concentration field of the greenhouse space include: Real-time acquisition of carbon dioxide concentration data, and adoption of sliding window filtering to eliminate random noise; Configuring a deviation threshold, calculating the absolute deviation of carbon dioxide concentration of adjacent grid nodes in the greenhouse space, and counting the number of sampling points of grid nodes with absolute deviation greater than the deviation threshold. If it is greater than the preset distribution anomaly threshold, it is determined that the carbon dioxide concentration distribution state in the greenhouse space is potentially uneven, otherwise it is determined to be evenly distributed; When it is determined that the carbon dioxide concentration distribution state in the greenhouse space is potentially uneven, the spatial position of the greenhouse space where the distributed grid nodes are located is obtained; Calculate the spatial distance between the interpolation point and all known grid nodes, and assign the weight in inverse proportion to the power function of the distance; Divide the levels and regions of the greenhouse space in combination with the three-dimensional spatial coordinate system of the greenhouse space; divide and exclude special regions of the greenhouse space; The carbon dioxide concentration of each level of grid nodes is stratified interpolated according to the weight of the interpolation point, and the interpolation points between levels are interpolated by calculating the concentration gradient in the vertical direction between levels; The specific steps of identifying the abnormal connected region and solving the target angle of the ventilation port and the target speed of the fan in the abnormal connected region include: Calculate the typical carbon dioxide concentration of the greenhouse space and each region by spatial statistical analysis, divide the connected regions of the carbon dioxide concentration field based on the spatial adjacency relationship and the similarity of the typical carbon dioxide concentration of each region, and calculate the geometric center, volume and typical carbon dioxide concentration of each connected region; By calculating the standard deviation and mean of the typical carbon dioxide concentration of all connected regions in the greenhouse space, the global spatial concentration variation coefficient is obtained. If the global spatial concentration variation coefficient is greater than the preset global threshold, local anomaly analysis is triggered: For each connected region, calculate the deviation rate of its typical carbon dioxide concentration and the typical concentration of the greenhouse space, and select the connected regions greater than the preset dynamic local threshold, and mark them as abnormal connected regions; Taking the geometric center of the abnormal connected region as a reference, extending outward along the concentration gradient direction, the position with a deviation rate of the typical carbon dioxide concentration from the typical concentration of the greenhouse space less than a dynamic local threshold is defined as the boundary of the abnormal connected region; Based on the spatial layout parameters of the ventilation openings and the fans in the greenhouse space, a gas flow concentration coupling physical model is constructed, an optimization objective is set according to the deviation rate of the abnormal connected region and the total energy consumption of the equipment, a double-objective optimization model is constructed, the decision variables include the fan speed and the ventilation opening angle, the constraint conditions include that the fan operating power is less than the rated power, and the double-objective optimization model is solved to obtain the target angle of the ventilation opening and the target speed of the fan in the greenhouse space.

2. The sugar-free seedling culture carbon dioxide monitoring system of claim 1, wherein, The specific steps of the modified carbon dioxide concentration interval and the positioning of the target carbon dioxide concentration include: A three-dimensional structured architecture of varieties, growth stages and environmental factors is adopted to construct a seedling environmental demand model library, which stores the basic biological parameters, carbon source demand parameters and environmental synergy threshold of the target seedling; The basic biological parameters include the photosynthetic compensation point, the photosynthetic saturation point and the carbon utilization efficiency curve; The carbon source demand parameters include the carbon dioxide concentration interval and the concentration fluctuation tolerance interval of each growth stage of the seedling; The environmental synergy threshold is used to define the interaction parameter of the environmental parameter; Based on the variety and growth stage of the target seedling, the basic carbon dioxide concentration interval of the corresponding growth stage is retrieved from the seedling environmental demand model library; Based on the current air temperature and air humidity, the air temperature and humidity synergy rule of the environmental synergy regulation rule is used to modify the basic carbon dioxide concentration interval; Based on the real-time light intensity, the light synergy rule of the environmental synergy regulation rule is used to position the target carbon dioxide concentration within the modified carbon dioxide concentration interval; The deviation degree of the target carbon dioxide concentration from the basic carbon dioxide concentration interval of the current growth stage in the seedling environmental demand model library is calculated, and if the deviation degree is greater than a preset deviation degree threshold, a concentration anomaly warning is triggered.

3. The sugar-free seedling culture carbon dioxide monitoring system as claimed in claim 2, wherein, The environmental synergy regulation rule includes the air temperature and humidity synergy rule and the light synergy rule; The air temperature and humidity synergy rule is used to adjust the target carbon dioxide concentration interval of the target seedling in the current growth stage based on the carbon dioxide concentration interval of the target seedling in the current growth stage through the air temperature and humidity condition, including: Based on the seedling environmental demand model library, the air temperature and humidity range of the target seedling in the current growth stage is obtained, including the photosynthetic temperature range and the transpiration humidity range; The air temperature and humidity of the greenhouse space are abnormally detected, and if there is an abnormality, the absolute deviation proportion is calculated according to the degree that the air temperature or air humidity exceeds the corresponding air temperature and humidity range, including the temperature absolute deviation proportion and the humidity absolute deviation proportion; According to the absolute deviation proportion, the target deviation proportion is selected, and the upper limit and the lower limit of the carbon dioxide concentration interval of the target seedling in the current growth stage are adjusted downward according to the target deviation proportion to modify the carbon dioxide concentration interval of the target seedling in the current growth stage.

4. The sugar-free seedling culture carbon dioxide monitoring system as claimed in claim 3, wherein, The light synergy rule is used to dynamically match the target carbon dioxide concentration based on the modified carbon dioxide concentration interval of the target seedling in the current growth stage according to the real-time light intensity. Based on the seedling environmental demand model library, the light saturation point threshold and the light compensation point threshold are obtained. When the real-time light intensity is greater than the light saturation point threshold, the target carbon dioxide concentration is positioned to the upper limit of the corrected carbon dioxide concentration interval; When the real-time light intensity is lower than the light compensation point threshold, the target carbon dioxide concentration is adjusted to the lower limit of the corrected carbon dioxide concentration interval; When the real-time light intensity is between the light compensation point threshold and the light saturation point threshold, the target carbon dioxide concentration is linearly adjusted according to the proportion of the light intensity to the light saturation point threshold and the light compensation point threshold.

5. The sugar-free seedling culture carbon dioxide monitoring system of claim 1, wherein, The specific steps of updating the adjustment direction and adjustment amplitude of the supply rate of the carbon dioxide supply unit include: Obtain the target carbon dioxide concentration and the typical carbon dioxide concentration of the greenhouse space, calculate the concentration deviation value, and obtain the fan speed, the ventilation opening angle, the volume of the greenhouse space, and the ventilation opening area; Based on the collected greenhouse space volume and the preset standard greenhouse space volume, the space coefficient is calculated according to the proportional relationship between the actual greenhouse space volume and the standard greenhouse space volume; Based on the total ventilation opening area and the surface area of the greenhouse space, the ventilation coefficient is calculated according to the proportional relationship between the total ventilation opening area and the surface area of the greenhouse space; Obtain the supply rate of the current carbon dioxide supply unit in the greenhouse space, which is used as the reference rate; Based on the positive and negative of the concentration deviation value, the adjustment direction is determined. When the concentration deviation value is positive, the adjustment direction is to increase the supply rate. When the concentration deviation value is negative, the adjustment direction is to reduce the supply rate.

6. The sugar-free seedling culture carbon dioxide monitoring system as claimed in claim 5, wherein, The specific steps of updating the adjustment direction and adjustment amplitude of the supply rate of the carbon dioxide supply unit also include: Retrieve the concentration fluctuation tolerance interval of the target seedling at the current growth stage, calculate the proportion of the concentration deviation value to the width of the concentration fluctuation tolerance interval as the basic adjustment proportion; Establish space mapping rules and ventilation mapping rules. The space mapping rules are used to establish the corresponding relationship between the space coefficient and the space correction gradient. The ventilation mapping rules establish the corresponding relationship between the ventilation coefficient and the ventilation correction multiple; Based on the space mapping rules and the ventilation mapping rules, the space correction gradient and the ventilation correction multiple are obtained, and the basic adjustment proportion is weighted and corrected as the target adjustment proportion; Multiply the target adjustment proportion by the reference rate of the current carbon dioxide supply unit to obtain the adjustment amplitude of the supply rate; Set a constraint value according to the rated power of the carbon dioxide supply unit to set a constraint condition. If the adjustment amplitude exceeds the constraint condition range, the adjustment amplitude is corrected according to the nearest constraint value.

7. The sugar-free seedling culture carbon dioxide monitoring system as claimed in claim 1, wherein, The specific steps of performing abnormal monitoring and optimization feedback include: After the adjustment direction and amplitude of the supply rate of the carbon dioxide supply unit are updated and issued, start the concentration field dynamic tracking, obtain the carbon dioxide distribution state in the greenhouse space, and the typical carbon dioxide concentration of the greenhouse space; Calculate the concentration deviation value and the deviation control duration of the concentration deviation value; Configure a concentration deviation threshold. When the concentration deviation value is greater than the concentration deviation threshold, enter the time limit judgment process to determine whether the deviation control duration of the concentration deviation value is greater than the preset control threshold. If yes, trigger an abnormal warning, and trigger an update according to the logic of uniform flow first and then supply adjustment; When the concentration deviation value is less than or equal to the concentration deviation threshold value, it is determined that the current regulation has made the concentration deviation return to a reasonable range, and the supply rate of the carbon dioxide supply unit is maintained.

8. A method for carbon dioxide regulation in sugar-free seedling culture, which is implemented based on the carbon dioxide monitoring system for sugar-free seedling culture according to any one of claims 1 to 7, characterized by, The application comprises: Step S1: collecting monitoring data in the greenhouse space through the distributed grid nodes, wherein the monitoring data comprises carbon dioxide concentration and environmental parameters; Step S2: judging whether the carbon dioxide concentration distribution state in the greenhouse space is potential unevenness based on the carbon dioxide concentration of the grid nodes, and if yes, constructing a carbon dioxide concentration field of the greenhouse space through layered interpolation based on the carbon dioxide concentration; the carbon dioxide concentration field is used to identify an abnormal connectivity region through connectivity analysis and double-discrimination index, and to solve the target angle of the ventilation opening and the target rotating speed of the fan in the abnormal connectivity region; Step S3: configuring target seedling carbon dioxide demand parameters and environmental collaborative regulation rules by constructing a seedling environmental demand model library, wherein the environmental collaborative regulation rules are used to correct the carbon dioxide concentration interval and locate the target carbon dioxide concentration according to the carbon dioxide demand parameters and the environmental parameters; Step S4: updating the adjustment direction and adjustment amplitude of the supply rate of the carbon dioxide supply unit according to the concentration deviation value of the greenhouse space, in combination with the space coefficient and the ventilation coefficient of the greenhouse space; Step S5: performing abnormal monitoring and optimization feedback on the supply rate of the carbon dioxide supply unit.

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