A soilless cultivation system based on a container plant factory

Abstract

The present application relates to the technical field of soilless culture control, and specifically provides a soilless culture system based on container plant factory planting, which comprises a cabin body and a planting rack arranged in the cabin body, further comprises a disinfection and sterilization system, an intelligent control system, a sensor network is distributed in the cabin body and is used for collecting environmental parameters in the cabin body in real time, a central controller is in communication connection with the disinfection and sterilization system, the central controller is configured to obtain information from the sensor network, generate a control instruction for the disinfection and sterilization system; the disinfection and sterilization system comprises an ozone generator, the sensor network comprises an infrared thermal imager, an environmental humidity sensor and an environmental temperature sensor, the leaf temperature is monitored in a non-contact mode through the infrared thermal imaging technology, the water stress index is calculated in combination with the environmental data, the thermal image features are analyzed, and the stomatal opening state of the plant is inferred; and the disinfection and sterilization opportunity and the ozone amount are precisely controlled.

Description

Technical Field

[0001] This invention relates to the field of soilless cultivation control technology, and specifically provides a soilless cultivation system based on container plant factory planting. Background Technology

[0002] Containerized plant factories, as a modern agricultural product with controllable environment, have shown broad application prospects in urban agriculture and extreme environment crop production in recent years. Their core advantage lies in their ability to achieve continuous crop production within a limited space, unaffected by external climatic conditions. Soilless cultivation, as the mainstream planting method in plant factories, significantly improves resource utilization efficiency and crop yield through precise control of water and fertilizer supply and environmental parameters.

[0003] However, in enclosed or semi-enclosed container environments, high-density planting and continuous production can easily lead to the accumulation and spread of pathogenic microorganisms. Traditional chemical disinfection methods pose a risk of residue and may adversely affect crop growth. Ozone, as a strong oxidizing gas, has excellent bactericidal and disinfection effects and leaves no residue after decomposition, and is gradually being introduced into the air disinfection of plant factories. However, most plant factories currently control ozone use based on a simple strategy of timed disinfection, which has problems such as improper disinfection timing, excessive or insufficient ozone, affecting crop growth. Summary of the Invention

[0004] To address the aforementioned shortcomings, this invention provides a soilless cultivation system based on containerized plant factories, aiming to solve the problems of inappropriate timing and difficulty in controlling the supply of ozone disinfection in existing plant factories.

[0005] To achieve the above objectives, the present invention provides a soilless cultivation system based on containerized plant factory cultivation, comprising a container and a planting rack disposed within the container, and further comprising...

[0006] Disinfection and sterilization system;

[0007] The intelligent control system includes a sensor network and a central controller that are interconnected. The sensor network is distributed within the cabin and is used to collect environmental parameters within the cabin in real time. The central controller is interconnected with the disinfection and sterilization system.

[0008] The disinfection and sterilization system includes an ozone generator, and the sensor network includes an infrared thermal imager, an ambient humidity sensor, and an ambient temperature sensor. The infrared thermal imager is positioned facing the plant canopy inside the cabin to collect thermal infrared data of the canopy and generate a thermal imaging video stream. The central controller is configured to acquire information from the sensor network and generate control commands for the disinfection and sterilization system.

[0009] Preferably, the control logic for the central controller to generate control commands for the disinfection and sterilization system is as follows:

[0010] A1. Extract thermal imaging image frames from the thermal imaging video stream at preset time intervals;

[0011] A2. Process the thermal imaging image frames to obtain image feature data related to the temperature distribution of plant leaves;

[0012] A3. Based on the image feature data and environmental temperature and humidity data, infer the stomatal aperture state S and water stress index C of the plant;

[0013] A4. Based at least on the stomatal opening state S, the moisture stress index C, and the humidity value RH in the environmental parameters, generate control commands and control the ozone generator according to the control commands.

[0014] Preferably, the "stomata opening state S" in step A3 is generated in the following way:

[0015] B1. Multiple image feature data extracted from the thermal imaging image frame are combined with data collected by the ambient temperature sensor and the ambient humidity sensor to construct a multi-dimensional input feature vector;

[0016] B2. Input the input feature vector into the pre-trained stomatal aperture prediction model;

[0017] B3. The stomatal aperture prediction model outputs the stomatal aperture state S.

[0018] Preferably, the sensor network further includes an ozone concentration sensor for real-time monitoring of ozone concentration inside the cabin.

[0019] Preferably, the specific logic for the central controller to execute step A4 is as follows:

[0020] The pore opening state S is compared with the preset threshold S of the opening state. 预 The water stress index C is compared with a preset threshold C of the water stress index. 预 The ambient humidity value RH is compared with a preset humidity threshold RH. 预 Compare;

[0021] If RH>RH 预 Or C <C 预 Or S>S 预 If so, the ozone generator will not be activated;

[0022] If RH≤RH 预 And C≥C 预 And S≤S 预The ozone generator is activated and the ozone concentration sensor readings are acquired in real time. The central controller controls the ozone generator to bring the ozone concentration inside the chamber to a set value T and stabilize it thereafter. 设 ;

[0023] Wherein, the ozone concentration set value T 设 It is generated based on the stomatal aperture state S, the moisture stress index C, and the humidity value RH in the environmental parameters.

[0024] Preferably, it also includes

[0025] An environmental control system is used to regulate the environment inside the cabin;

[0026] A water and fertilizer irrigation system is used to provide nutrients to plants;

[0027] The environmental control system includes a supplemental lighting module, a temperature control module, a humidity control module, a ventilation module, and a CO2 replenishment module;

[0028] The water and fertilizer irrigation system includes a nutrient solution preparation unit and a drip irrigation unit;

[0029] The central controller is configured to integrate data from the sensor network and perform linked closed-loop control of the environmental control system and the water and fertilizer irrigation system.

[0030] Preferably, when executing control commands to the disinfection and sterilization system, the central controller is further configured to:

[0031] Turn off the ventilation module and the full-spectrum light source of the supplemental lighting module, and turn on only the far-red light source to emit far-red light with a wavelength of 730-760nm to the plant canopy. After irradiation for a preset time, execute the control process of steps A1 to A4.

[0032] Preferably, the ventilation module integrates a UV-C ultraviolet lamp within its air duct;

[0033] The central controller is also configured to: control the ozone generator to operate for a preset time period and then shut it off; start the ventilation module and circulate the air inside the cabin; simultaneously start the UV-C ultraviolet lamp; acquire the reading of the ozone concentration sensor in real time; and generate a command to shut off the UV-C ultraviolet lamp when the ozone concentration drops to a preset safe concentration threshold.

[0034] Preferably, the cabin includes a food-grade stainless steel inner layer and a polyurethane insulation layer.

[0035] The purpose of this invention is to provide a soilless cultivation system based on containerized plant factories, which has the following beneficial effects:

[0036] ① This system uses infrared thermal imaging technology to monitor leaf temperature non-contactly and calculates the water stress index in combination with environmental data. At the same time, it uses a trained prediction model to analyze thermal image features and infer the stomatal opening status of plants. The central controller makes decisions and only starts the ozone generator during safe periods, thereby effectively disinfecting and sterilizing while minimizing stress on plant physiology, achieving precise control of disinfection timing and ozone quantity.

[0037] ② This system achieves precise control of the crop growth environment by setting up a sealed chamber, modular environmental control and intelligent water and fertilizer management; the integrated food-grade heat preservation chamber, customizable spectrum LED supplemental lighting, air conditioning temperature control, CO2 supplementation and UV disinfection drip irrigation and other functions work together to ensure that crops are in the best growth conditions and get rid of dependence on the external environment and pesticides. Attached Figure Description

[0038] Figure 1 This is an overall schematic diagram of a soilless cultivation system based on containerized plant factories;

[0039] Figure 2 This is the control logic diagram of the central controller of the present invention for the disinfection and sterilization system;

[0040] In the diagram:

[0041] 10-Environmental control system; 100-Supplemental lighting module; 101-Temperature control module; 102-Humidity control module; 103-Ventilation module; 104-CO2 supplementation module;

[0042] 20-Water and fertilizer irrigation system;

[0043] 30 - Disinfection and sterilization system;

[0044] 40 - Intelligent control system; 400 - Sensor network; 4001 - Infrared thermal imager; 4002 - Ambient humidity sensor; 4003 - Ambient temperature sensor; 4004 - Ozone concentration sensor; 4005 - Light sensor; 401 - Central controller.

[0045] 50 - Display interface. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0047] like Figure 1-2As shown, a hydroponics system based on containerized plant factories includes a container body. The inner layer of the container is made of food-grade stainless steel, which has good corrosion resistance and is easy to clean. The middle layer is a polyurethane insulation layer, which effectively blocks external heat exchange, maintains a stable internal environment, and improves energy efficiency. Planting racks are installed inside the container. The frames of the planting racks are made of galvanized pipe, which is easy to install and has a strong load-bearing capacity.

[0048] The cabin is equipped with an environmental control system 10 to regulate the climate environment inside the cabin. Specifically, the environmental control system mainly includes a supplementary lighting module 100, a temperature control module 101, a humidity control module 102, a ventilation module 103, and a CO2 supplementation module 104. The supplementary lighting module 100 is usually an LED plant growth light. The spectrum of the LED plant growth light is mainly red light with a wavelength of 660nm and blue light with a wavelength of 450nm. The spectrum can also be customized according to the type of crop and its growth stage.

[0049] The supplementary lighting module 100 also includes a far-infrared lamp, which can emit far-infrared light with a wavelength of 730-760nm.

[0050] It also features a temperature control module 101, which uses an air conditioner and heating device to stabilize the temperature within a suitable range of 20-25℃ during the day and 19-22℃ at night. Of course, this is just a general range, and users can adapt different temperature ranges according to different plants.

[0051] The humidity control module 102 maintains air humidity within the optimal range using a humidifier and dehumidifier, preventing the plant's growing environment from becoming too dry or too humid. The ventilation module 103 includes a fan and a micro-wind system, ensuring indoor air circulation, preventing localized CO2 deficiency or uneven humidity, and simultaneously expelling water vapor and heat generated by plant respiration. The CO2 replenishment module 104 releases CO2 through a gas cylinder. During peak photosynthesis periods, the system replenishes carbon dioxide, increasing its concentration to a certain level to enhance the efficiency of plant photosynthesis.

[0052] The cabin is also equipped with a water and fertilizer irrigation system 20, which includes a nutrient solution preparation unit and a drip irrigation unit. Based on monitoring data such as EC and pH values, it automatically adds fertilizer and uses a UV disinfection device to ensure the nutrient solution is sterile, preventing the spread of diseases through the liquid. The drip irrigation unit automatically irrigates based on monitoring data, delivering the nutrient solution directly to the plant roots.

[0053] The container is also equipped with a disinfection and sterilization system 30. Because the container itself is a closed environment, it can effectively isolate external pathogens and pests. Therefore, the planting process is completely free from pesticides and herbicides. In addition to disinfecting and sterilizing the nutrient solution, ozone can also be introduced to disinfect the air inside the container.

[0054] The cabin is also equipped with an intelligent control system 40, which includes a sensor network 400 distributed within the cabin. This sensor network is used to collect environmental parameters in real time, including at least temperature, humidity, light intensity, CO2 concentration, pH value, EC value, and ozone concentration. The sensor network 400 is communicatively connected to a central controller 401, which is configured to receive and process the environmental parameters and generate control commands based on the processing results. The central controller 401 is communicatively connected to the environmental control system 10, the water and fertilizer irrigation system 20, and the disinfection and sterilization system 30.

[0055] The EC value represents the concentration of soluble ions in the planting medium.

[0056] As a further explanation of this embodiment, the disinfection and sterilization system 30 includes an ozone generator, and the sensor network 400 includes at least an infrared thermal imager 4001 and an ambient humidity sensor 4002. The infrared thermal imager 4001 is fixedly installed facing the plant canopy inside the chamber to continuously collect infrared thermal imaging data of the plant leaves; the ambient humidity sensor 4002 is located at a representative position inside the chamber to monitor the air humidity inside the chamber in real time, providing a basis for the analysis of the thermal imaging data.

[0057] In addition, the sensor network 400 also includes an ambient temperature sensor 4003 for collecting the temperature inside the cabin environment; and an ozone concentration sensor 4004 for real-time monitoring of the ozone concentration inside the cabin.

[0058] Preferably, the sensor network 400 further includes a light sensor 4005 for detecting the light intensity inside the cabin.

[0059] The ozone generator, infrared thermal imager 4001, ambient humidity sensor 4002, and ambient temperature sensor 4003 are connected to the central controller 401 via wired or wireless communication, forming a closed-loop feedback control system.

[0060] As a further explanation of this embodiment, the control logic of the central controller 401 generating control commands for the disinfection and sterilization system 30 is as follows:

[0061] A1. Extract thermal imaging image frames from the thermal imaging video stream at preset time intervals;

[0062] Specifically, a sampling time interval is preset in the central controller 401, which can be set to 30 seconds. Every time the time interval is elapsed, that is, every 30 seconds, the central controller 401 will immediately send a "capture" command to the video stream that is being transmitted. This command will capture the video image that is being transmitted at the current moment.

[0063] A2. Process the thermal imaging image frames to obtain image feature data related to the temperature distribution of plant leaves;

[0064] The central controller 401 calls the image processing algorithm to analyze the captured thermal imaging image frame: first, it identifies and segments the plant area, eliminates the interference of the background planting rack and the ground, and then calculates the statistical characteristics, mainly including the average temperature of the entire canopy, the standard deviation of the canopy temperature, and the difference between the average temperature of the canopy and the reading of the ambient temperature sensor 4003 at the same time.

[0065] A3. Based on the image feature data and environmental temperature and humidity data, infer the stomatal aperture state S and water stress index C of the plant;

[0066] A4. Based at least on the stomatal opening state S, the moisture stress index C, and the humidity value RH in the environmental parameters, generate control commands and control the operation of the ozone generator according to the control commands.

[0067] Specifically, the pore opening state S is compared with the preset threshold S of the opening state. 预 The water stress index C is compared with a preset threshold C of the water stress index. 预 The ambient humidity value RH is compared with a preset humidity threshold RH. 预 Compare.

[0068] If RH>RH 预 Regardless of the stomatal opening state S and the water stress index C, a control command is generated to prohibit the ozone generator from releasing ozone. This is because if ozone is released at this time, it will react under high humidity conditions, generating excessive hydroxyl radicals that will damage the protective layer and epidermal cells of plant leaves.

[0069] If C <C 预 Regardless of the stomatal opening state S and the ambient humidity value RH, a control command is generated to prevent the ozone generator from releasing ozone. On the one hand, a low water stress index indicates that the crop is not short of water and transpiration is proceeding normally, so the stomatal opening will gradually increase. On the other hand, when transpiration is strong, a thin water film will cover the surface of the plant leaves, which will also react with ozone to generate excessive hydroxyl radicals.

[0070] If S>S 预 Regardless of the water stress index C and the ambient humidity value RH, a control command will be generated to prohibit the ozone generator from releasing ozone, because ozone will directly enter the plant through the open stomata and oxidize the internal cell tissue.

[0071] In other words, only when RH≤RH 预 And C≥C 预 And S≤S预 At that time, a control command is generated to allow the ozone generator to release ozone, and the reading of the ozone concentration sensor 4004 is acquired in real time. The control command of the central controller 401 causes the ozone generator to operate, so that the ozone concentration in the chamber reaches and stabilizes at the ozone concentration set value T. 设 The ozone concentration setpoint T 设 It is generated based on the stomatal aperture state S, the moisture stress index C, and the humidity value RH in the environmental parameters.

[0072] Preferably, the ozone concentration setpoint T 设 The calculation method is as follows:

[0073] ;

[0074] Where, f(S) = 1 - (S / S) 预 f(C) = 1 - (C) 预 / C), f(RH)=1-(RH / RH) 预 ).

[0075] Where W1, W2, and W3 are the weighting coefficients of each parameter, and W1 + W2 + W3 = 1.

[0076] In high humidity environments, the risks associated with increased stomatal opening are amplified. Therefore, we can introduce an interaction factor λ to correct the ozone concentration setpoint T. 设 The calculation method is as follows:

[0077] ;

[0078] Tmax is the upper limit of ozone concentration. Considering that crops may be more vulnerable when the environment is not in the ideal state for crop growth, the upper limit of ozone concentration can be appropriately reduced by using parameters such as the current temperature and CO2 concentration to provide additional safety redundancy.

[0079] As a further explanation of this embodiment, the "stomata opening state S" in step A3 is generated as follows:

[0080] B1. Multiple image feature data extracted from the thermal imaging image frame are combined with data collected by the ambient temperature sensor 4003 and the ambient humidity sensor 4002 to construct a multi-dimensional input feature vector; the image feature data must include at least the average temperature of the plant canopy, the standard deviation of the temperature, and the temperature difference between the average temperature of the canopy and the air temperature;

[0081] B2. Input the input feature vector into the pre-trained stomatal aperture prediction model;

[0082] B3. The stomatal aperture prediction model outputs the stomatal aperture state S.

[0083] The stomatal aperture prediction model needs to be trained, for example, by deploying a sensor network and a stomatal meter in a plant factory experimental chamber. During multiple planting cycles, sensor readings and actual stomatal conductance measured by the stomatal meter are recorded simultaneously at fixed time intervals. The fixed time interval can be set to 5 minutes. The collected raw data is then cleaned, removing missing and outlier values. Predefined features are extracted from the thermal imaging data at each time point, including the average plant canopy temperature, the standard deviation of canopy temperature, and the temperature difference between the canopy and the air. These features are then combined with the ambient temperature and relative humidity readings at that time point to form an initial feature vector.

[0084] Then, the feature vector at each time point is paired with its corresponding stomatal aperture ground truth label to construct a structured dataset.

[0085] Finally, the model needs to be trained. A supervised machine learning algorithm is chosen, and this approach uses a gradient boosting decision tree. The training set is input into the algorithm, and the model learns the mapping relationship between feature vectors and stomata opening by minimizing the error between the predicted values ​​and the true labels. During training, a validation set is used to monitor the training progress and find the optimal model configuration.

[0086] The formula for calculating the water stress index C is as follows:

[0087] C=(ΔT1-ΔT ca ) / (ΔT u -ΔT ca );

[0088] In the above formula, ΔT l It is the actual temperature difference between the crop canopy temperature and the air temperature; ΔT ca This refers to the lower limit of the temperature difference under theoretically stress-free conditions when the plant has sufficient water; ΔT u It is the upper limit of the temperature difference under severe water shortage, which is also the theoretical maximum stress.

[0089] As can be seen from the formula above, a higher C indicates that the crop is short of water, and the stomata on the leaves will partially or completely close to reduce water loss, meaning the stomatal opening will gradually decrease. A lower C indicates that the crop is not short of water, transpiration is proceeding normally, and the stomatal opening will gradually increase.

[0090] As a further explanation of this embodiment, when executing the ozone sterilization control logic, the central controller 401 is also configured to:

[0091] The ventilation module 103 is turned off, the full-spectrum light source of the supplementary lighting module 100 is turned off, and only its far-red light band light source is turned on to emit far-red light with a wavelength of 730-760nm to the plant canopy. After the far-red light is irradiated for a preset time, the control process of steps A1 to A4 is executed.

[0092] Far-red light in the 730-760nm range is an active "signal light" that counteracts the effect of red light on stomatal opening by acting on the photosensitive pigment system. The stomatal opening effect previously induced by red light is reversed, thereby indirectly reducing the stomatal aperture.

[0093] For example, if the plan is to use ozone to disinfect and sterilize the air inside the plant factory every Monday morning at 8:00 AM, then at 8:00 AM on Monday, first turn off the ventilation module 103 and the full-spectrum light source of the supplementary lighting module 100, only turning on its far-infrared light source. After 20 minutes of far-infrared light irradiation, the central controller 401 starts working and executes the control process described in steps A1 to A4. Afterwards, if the central controller 401 controls the ozone generator to make the ozone concentration inside the chamber reach and stabilize at the ozone concentration setpoint T... 设 If the system records that the disinfection and sterilization task for this week has been completed, and sets the disinfection and sterilization process to be repeated one week later, if the central controller 401 determines that the current environment cannot start the ozone generator after 20 minutes of far-red light irradiation, then the far-red light irradiation time will be extended, for example, by another ten minutes on the basis of the previous time. Then the central controller 401 will start working and execute the control process of steps A1 to A4. If it is still determined that the ozone generator will not be started, then the normal production mode will be restored and the disinfection and sterilization process will be postponed to 8:00 a.m. of the next day.

[0094] As a further explanation of this embodiment, the ventilation module 103 integrates a UV-C ultraviolet lamp in its air duct.

[0095] The central controller 401 is also configured to: control the ozone generator to run for a preset time period and then turn it off, the preset time period being 30 minutes; then start the ventilation module 103 and circulate the air in the cabin; simultaneously start the UV-C ultraviolet lamp; acquire the reading of the ozone concentration sensor 4004 in real time; and when the ozone concentration drops to a preset safe concentration threshold, generate a command to turn off the UV-C ultraviolet lamp.

[0096] Specifically, after ozone sterilization, to avoid affecting crop growth, the ozone needs to be decomposed. The central controller 401 first activates the fan of the ventilation module 103, forcing the air inside the chamber to circulate through the air duct integrated with UV-C ultraviolet lamps, and then powers on the UV-C lamps in the air duct. The ozone-containing air is blown by the fan through the air duct area filled with UV-C photons, and the ozone molecules are rapidly decomposed into oxygen under the irradiation of UV-C. The purified air is then blown back into the chamber, and this cycle continues until the ozone concentration inside the chamber drops to a safe threshold. Then, the full-spectrum light source of the supplemental lighting module 100 can be turned on, and the crops return to their normal growth mode.

[0097] Preferably, the central controller 401 is further configured to:

[0098] The thermal imaging video stream acquired by the infrared thermal imager 4001 is processed in real time and output to a display interface 50 for dynamic visualization.

[0099] The display interface 50 adopts a partitioned display layout, including at least a main display area, for real-time display of pseudo-color encoded thermal imaging video streams, with different colors representing different temperature distributions;

[0100] Preferably, the display interface 50 further includes a parameter overlay display area, which displays the current leaf temperature data, environmental parameters, and the inferred stomatal opening state S in real time on the thermal imaging screen in the form of overlaid numbers or charts.

[0101] Preferably, the display interface 50 is further provided with user interaction controls for setting temperature alarm thresholds, vent status safety thresholds and equipment control parameters, and providing system alarm prompts and operation log query functions.

[0102] This invention is not limited to the specific embodiments described above. Any modifications made by those skilled in the art based on the above concept without creative effort are within the scope of protection of this invention.

Claims

1. A soilless cultivation system based on containerized plant factory planting, comprising a container and planting racks disposed within the container, characterized in that, Also includes: Disinfection and sterilization system (30); The intelligent control system (40) includes a sensor network (400) and a central controller (401) that are interconnected. The sensor network (400) is distributed in the cabin and is used to collect environmental parameters in the cabin in real time. The central controller (401) is interconnected with the disinfection and sterilization system (30). The disinfection and sterilization system (30) includes an ozone generator, and the sensor network (400) includes an infrared thermal imager (4001), an ambient humidity sensor (4002), and an ambient temperature sensor (4003). The infrared thermal imager (4001) is positioned facing the plant canopy inside the cabin to collect thermal infrared data of the canopy and generate a thermal imaging video stream. The central controller (401) is configured to obtain information from the sensor network (400) and generate control commands for the disinfection and sterilization system (30). The control logic of the central controller (401) for generating control commands to the disinfection and sterilization system (30) is as follows: A1. Extract thermal imaging image frames from the thermal imaging video stream at preset time intervals; A2. Process the thermal imaging image frames to obtain image feature data related to the temperature distribution of plant leaves; A3. Based on the image feature data and environmental temperature and humidity data, infer the stomatal aperture state S and water stress index C of the plant; A4. Based at least on the stomatal opening state S, the moisture stress index C, and the humidity value RH in the environmental parameters, generate control commands and control the ozone generator according to the control commands. The "stomata opening state S" in A3 is generated as follows: B1. Multiple image feature data extracted from the thermal imaging image frame are combined with the data collected by the ambient temperature sensor (4003) and the ambient humidity sensor (4002) to construct a multi-dimensional input feature vector; B2. Input the input feature vector into the pre-trained stomatal aperture prediction model; B3. The stomatal aperture prediction model outputs the stomatal aperture state S.

2. The soilless cultivation system based on containerized plant factory planting according to claim 1, characterized in that, The sensor network (400) also includes an ozone concentration sensor (4004) for real-time monitoring of ozone concentration inside the cabin.

3. The soilless cultivation system based on containerized plant factory planting according to claim 2, characterized in that, The specific logic for the central controller (401) to execute step A4 is as follows: The pore opening state S is compared with the preset threshold S of the opening state. 预 The water stress index C is compared with a preset threshold C of the water stress index. 预 Compare the ambient humidity value (RH) with the preset humidity threshold (RH). 预 Compare; If RH>RH 预 Or C <C 预 Or S>S 预 If so, the ozone generator will not be activated; If RH≤RH 预 And C≥C 预 And S≤S 预 The ozone generator is started and the readings of the ozone concentration sensor (4004) are acquired in real time. The central controller (401) controls the ozone generator to make the ozone concentration in the cabin reach and stabilize at the ozone concentration set value T. 设 ; Wherein, the ozone concentration set value T 设 It is generated based on the stomatal aperture state S, the moisture stress index C, and the humidity value RH in the environmental parameters.

4. The soilless cultivation system based on containerized plant factory planting according to claim 3, characterized in that, Also includes An environmental control system (10) is used to regulate the environment inside the cabin; A water and fertilizer irrigation system (20) is used to provide nutrients to plants; The environmental control system (10) includes a supplementary lighting module (100), a temperature control module (101), a humidity control module (102), a ventilation module (103), and a CO2 supplementation module (104). The water and fertilizer irrigation system (20) includes a nutrient solution preparation unit and a drip irrigation unit; The central controller (401) is configured to integrate data from the sensor network (400) to perform linked closed-loop control of the environmental control system (10) and the water and fertilizer irrigation system (20).

5. The soilless cultivation system based on containerized plant factory planting according to claim 4, characterized in that, When executing control commands to the disinfection and sterilization system (30), the central controller (401) is also configured to: The ventilation module (103) is turned off, the full-spectrum light source of the supplementary lighting module (100) is turned off, and only the far-red light band light source is turned on to emit far-red light with a wavelength of 730-760nm to the plant canopy. After irradiation for a preset time, the control process A1 to A4 is executed.

6. The soilless cultivation system based on containerized plant factory planting according to claim 5, characterized in that, The ventilation module (103) integrates a UV-C ultraviolet lamp in its air duct; The central controller (401) is also configured to: control the ozone generator to run for a preset time period and then shut it off; start the ventilation module (103) and circulate the air inside the cabin; simultaneously start the UV-C ultraviolet lamp; obtain the reading of the ozone concentration sensor (4004) in real time; and generate a command to shut off the UV-C ultraviolet lamp when the ozone concentration drops to a preset safe concentration threshold.

7. The soilless cultivation system based on containerized plant factory planting according to claim 1, characterized in that, The cabin consists of a food-grade stainless steel inner layer and a polyurethane insulation layer.

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