A system and method for coordinated regulation of water, fertilizer and environment in tidal greenhouse seedling cultivation

Abstract

This invention belongs to the field of seedling cultivation control technology and provides a system and method for coordinated regulation of water, fertilizer and environment in tidal greenhouse seedling cultivation. This invention constructs a robust seedling evaluation model and a robust seedling model library, obtains seedling phenotypic indicators, environmental factors and substrate moisture content in real time, calculates the robust seedling index deviation, and uses this as the core feedback quantity to link and regulate tidal irrigation and greenhouse environment, so as to achieve closed-loop control of seedling condition, environment and water and fertilizer.

Description

Technical Field

[0001] This invention belongs to the field of seedling cultivation control technology, specifically relating to a tidal greenhouse seedling water, fertilizer and environmental synergistic control system and method. Background Technology

[0002] Tidal seedling raising refers to using the principle of tidal rise and fall to provide seedlings with a uniform supply of water and nutrients through periodic immersion and drainage of the substrate. However, existing technologies have the following problems: 1. Existing tidal seedling cultivation methods mostly irrigate according to fixed irrigation cycles and experience settings, and at most, simply control the start and stop of irrigation by combining substrate moisture content or EC threshold.

[0003] 2. Seedling cultivation goals often focus only on "not dying" and "growing fast," lacking a comprehensive evaluation model for robust seedlings based on multiple indicators such as "plant height, stem diameter, leaf area, and dry matter," resulting in problems such as uniform but weak seedlings, excessive growth, or poor root systems.

[0004] 3. Environmental control (temperature, humidity, light) is usually separated from irrigation control, lacking a negative feedback loop based on the seedling vigor model, and cannot adjust the environment and tidal irrigation strategy according to the dynamic condition of the seedlings. Therefore, a negative feedback regulation method is needed that couples the seedling evaluation model, tidal irrigation parameters, and greenhouse environmental factors to achieve refined seedling cultivation aimed at achieving robust seedlings. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a tidal greenhouse seedling cultivation water, fertilizer, and environmental synergistic control system and method to solve the problems in the prior art. The technical solution adopted by this invention is as follows: A tidal greenhouse seedling water, fertilizer and environment coordinated regulation system includes: an environment and substrate monitoring module, a seedling phenotypic acquisition device, a data acquisition and preprocessing unit, a negative feedback decision and controller, a tidal irrigation execution mechanism and an environmental regulation execution mechanism; The environment and substrate monitoring module and the seedling phenotypic acquisition device are used to collect environmental data, substrate water and fertilizer data and phenotypic data, and upload them to the data acquisition and preprocessing unit. The data acquisition and preprocessing unit outputs the current seedling strength index based on the seedling strength evaluation model, and simultaneously queries the seedling strength model library to obtain the target seedling strength index. The negative feedback decision and controller generates control quantities based on the deviation between the current seedling strength index and the target seedling strength index, as well as the environmental and substrate deviations, and drives the tidal irrigation actuator and the environmental control actuator to achieve coordinated regulation of water, fertilizer and environment.

[0006] Furthermore, the robust seedling evaluation model is expressed as the following formula: SI = Σ(k=1..K) w_k·PC_k Let the seedling phenotypic index vector be X = [H, D, N, A, W]. T Where H is plant height, D is stem diameter, N is number of leaves, A is leaf area, and W is dry matter content; the i-th index is standardized as follows: z_i = (x_i - μ_i) / σ_i A comprehensive evaluation is established using principal component analysis: the k-th principal component PC_k=Σ(i=1..m) a(k,i)·z_i, where a(k,i) is the loading coefficient; the corresponding eigenvalue is λ_k, and the contribution rate weight w_k = λ_k / Σ(j=1..K) λ_j.

[0007] Furthermore, the environment and substrate monitoring module includes an air temperature sensor, a relative humidity sensor, a light intensity sensor, an EC / PH sensor, a tidal bed water level sensor, and a return water flow meter.

[0008] Furthermore, the seedling phenotypic acquisition device includes a top / side view camera, a depth camera, or a ruler measuring device.

[0009] Furthermore, the tidal irrigation actuator includes a storage tank, a water pump, a solenoid valve, and inlet and outlet water pipes for the tidal bed, to achieve timed high and low tides in the seedling bed.

[0010] Furthermore, the environmental control actuators include fans, wet curtains, heating furnaces, and sunshades.

[0011] A tidal seedling raising method includes: S1: Construction and database building of the robust seedling model: Seedling cultivation experiments were conducted in an experimental greenhouse with different combinations of environmental factors and substrate moisture content. Plant height, stem diameter, leaf area, and dry matter content were periodically measured. Combined with environmental and substrate data, principal component analysis / factor analysis was used to establish a seedling vigor evaluation model. Define the environment and matrix state vectors: Env_now=[T, RH, L, θ, EC] T Where T is air temperature, RH is relative humidity, L is light intensity, θ is substrate moisture content, and EC is the electrical conductivity of the substrate or nutrient solution; the reference vector is obtained from the robust seedling model library: Env_ref=[T_ref, RH_ref, L_ref, θ_ref, EC_ref] T ; The environment-matrix deviation vector is: ΔEnv = Env_now - Env_ref; The seedling strength index deviation ΔSI and the environment / substrate deviation ΔEnv are combined to form an error vector: e = [ΔSI, ΔEnv] T ] T The control quantity is generated by using a negative feedback control law: Δu: Δu = -K·e, where K is the adjustable gain matrix; Map the control input to a control parameter vector: u = [h, τ_flood, τ_int, EC_nut, T_set, RH_set, L_set] T These correspond to the tidal level h, the duration of high tide τ_flood, the irrigation interval τ_int, the nutrient solution EC setting value EC_nut, and the greenhouse temperature, humidity and light setting values, respectively. The parameter update is constrained: u_{k+1} = sat(u_k + Δu, u_min, u_max), where sat(·) represents the saturation constraint on the upper and lower limits; Select the best-performing treatment group, extract the corresponding multi-factor time series, construct strong seedling model curves for different crops and seedling ages, and store them in the strong seedling model library. S2: Initialization before seedling raising: Sensors and camera / measuring devices are deployed in the tidal seedling greenhouse; Select the target crop and cultivation method in the human-computer interface, and load the corresponding seedling strengthening mode; Set permissible limits for tidal irrigation and upper and lower safety limits for greenhouse equipment; S3: Data Acquisition During Operation: The controller executes tidal irrigation and environmental settings according to the preset initial mode; Periodically collect environmental factors, substrate moisture content, and tidal operation data; Collect seedling images / phenotypic data on a daily or multi-day cycle, and calculate the current seedling vigor index SI_now; S4: Calculation of Seedling Strength Index and Environmental Deviation: Based on the seedling age, obtain the target seedling strength index SI_target and the corresponding environmental / substrate reference value for that period from the seedling strength model library; Calculate the seedling strength index deviation ΔSI = SI_now - SI_target; Calculate the environment and matrix deviation vector ΔEnv; S5: Generation of negative feedback control quantity: Using ΔSI and ΔEnv as inputs, the negative feedback decision module is invoked; If ΔSI>0 and seedlings are growing excessively: reduce irrigation frequency or shorten tidal duration, lower nighttime temperature, and increase light intensity; If ΔSI < 0 and the seedlings are weak: increase the frequency / duration of tides, and increase the substrate moisture content and nutrient solution concentration; The control results are converted into tidal irrigation parameter adjustment amounts and environmental setpoint offsets. S6: Execution and Cyclic Correction: Control the tidal irrigation actuators and environmental control actuators to operate according to the new parameters; SI_now is recalculated in the next observation period and compared with the previous period to form a trend judgment; If ΔSI remains within the threshold for multiple cycles, the current control strategy is maintained; otherwise, iterative updates continue. S7: End Phase and Mode Output: When the seedlings reach the stage of being ready for transplanting, test whether the seedling vigor index meets the standard for strong seedlings. Output the parameter trajectory of the entire process of this batch of tidal irrigation and environmental control.

[0012] The present invention has the following beneficial effects: (1) Unlike traditional control based on a single environmental threshold or a single moisture index, this invention uses the seedling index output by a seedling evaluation model constructed from multiple indicators to drive regulation. (2) This invention integrates the duration of high tide, irrigation interval, flooding depth, nutrient solution EC and environmental factors such as temperature, humidity and light into a set of negative feedback algorithms to form a coupled control closed loop of seedling condition, environment and tidal water and fertilizer. (3) The present invention has independent seedling growth model curves for different crops and seedling age stages. The system can iteratively correct the model parameters based on actual operating data to improve cross-variety and cross-season adaptability. Attached Figure Description

[0013] Figure 1 This is a diagram showing the overall structure of the system of the present invention; Figure 2 This is a flowchart of the method of the present invention. Detailed Implementation

[0014] The following will be described in conjunction with embodiments of the present invention. Figures 1-2 The technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Unless otherwise specified, the technical means used in the embodiments are conventional means well known to those skilled in the art.

[0015] This invention constructs a robust seedling evaluation model and a robust seedling model library, acquires seedling phenotypic indicators, environmental factors and substrate moisture content in real time, calculates the robust seedling index deviation, and uses this as the core feedback quantity to link and adjust tidal irrigation (water level, duration, interval, nutrient solution concentration) and greenhouse environment (temperature, humidity, light) to achieve closed-loop control of seedling condition, environment, water and fertilizer.

[0016] like Figure 1 As shown, the present invention provides a tidal greenhouse seedling water, fertilizer and environment synergistic control system, including: an environment and substrate monitoring module, a seedling phenotypic acquisition device, a data acquisition and preprocessing unit, a negative feedback decision and controller, a tidal irrigation execution mechanism and an environmental control execution mechanism; The environment and substrate monitoring module and the seedling phenotypic acquisition device are used to collect environmental data, substrate water and fertilizer data and phenotypic data, and upload them to the data acquisition and preprocessing unit. The data acquisition and preprocessing unit outputs the current seedling strength index based on the seedling strength evaluation model, and simultaneously queries the seedling strength model library to obtain the target seedling strength index. The negative feedback decision and controller generates control quantities based on the deviation between the current seedling strength index and the target seedling strength index, as well as the environmental and substrate deviations, and drives the tidal irrigation actuator and the environmental control actuator to achieve coordinated regulation of water, fertilizer and environment.

[0017] Furthermore, the robust seedling evaluation model is expressed as the following formula: SI = Σ(k=1..K) w_k·PC_k Let the seedling phenotypic index vector be X = [H, D, N, A, W]. T Where H is plant height, D is stem diameter, N is number of leaves, A is leaf area, and W is dry matter content; the i-th index is standardized as follows: z_i = (x_i - μ_i) / σ_i A comprehensive evaluation is established using principal component analysis: the k-th principal component PC_k=Σ(i=1..m) a(k,i)·z_i, where a(k,i) is the loading coefficient; the corresponding eigenvalue is λ_k, and the contribution rate weight w_k = λ_k / Σ(j=1..K) λ_j.

[0018] Furthermore, the environment and substrate monitoring module includes an air temperature sensor, a relative humidity sensor, a light intensity sensor, an EC / PH sensor, a tidal bed water level sensor, and a return water flow meter. These are used to collect real-time environmental and water / fertilizer status data during the tidal seedling cultivation process.

[0019] Furthermore, the seedling phenotypic acquisition device includes a top / side view camera, a depth camera, or a ruler-like measuring device. It is used to acquire indicators such as plant height, stem diameter, number of leaves, and leaf area.

[0020] Furthermore, the tidal irrigation actuator includes a storage tank, a water pump, a solenoid valve, and inlet and outlet water pipes for the tidal bed, used to realize the timed rise and fall of the tide in the seedling bed. It is preferably driven by a PLC or embedded controller, but is not limited to IoT or Zigbee networking methods.

[0021] Furthermore, the environmental control actuators include fans, wet curtains, heating furnaces, and sunshades.

[0022] Furthermore, it also includes a human-computer interaction and mode management module, which provides an interface for crop selection, seedling vigor mode selection and parameter adjustment, and displays seedling vigor index curves, environmental curves and irrigation records, facilitating manual intervention and optimization.

[0023] like Figure 2 The present invention also proposes a tidal seedling raising method, comprising: S1: Construction and database building of the robust seedling model: 1. Conduct seedling cultivation experiments on processing tomatoes, melons, etc., by setting up different combinations of environmental factors and substrate moisture content in the experimental greenhouse; 2. Periodically measure phenotypic and physiological indicators such as plant height, stem diameter, leaf area, and dry weight. Combined with environmental and substrate data, principal component analysis / factor analysis is used to establish a robust seedling evaluation model, and robust seedling thresholds and grades are given. Define the environment and matrix state vectors as Env_now=[T, RH, L, θ, EC]. T Where T is air temperature, RH is relative humidity, L is light intensity, θ is substrate moisture content, and EC is the electrical conductivity of the substrate or nutrient solution. The reference vector Env_ref=[T_ref, RH_ref, L_ref, θ_ref, EC_ref] is obtained from the seedling model library. T .

[0024] The environment-matrix deviation vector is: ΔEnv = Env_now - Env_ref.

[0025] The seedling strength index deviation ΔSI and the environment / substrate deviation ΔEnv are combined to form an error vector e = [ΔSI, ΔEnv]. T ] T The control quantity Δu is generated by using a negative feedback control law: Δu = -K·e, where K is the adjustable gain matrix (or equivalent weight coefficient vector).

[0026] Map the control input to a control parameter vector u = [h, τ_flood, τ_int, EC_nut, T_set, RH_set, L_set]. T These correspond to the tidal level h, the flood tide duration τ_flood, the irrigation interval τ_int, the nutrient solution EC setting value EC_nut, and the greenhouse temperature, humidity, and light setting values, respectively.

[0027] The parameter update is constrained: u_{k+1} = sat(u_k + Δu, u_min, u_max), where sat(·) represents the saturation constraint on the upper and lower limits, and u_min and u_max are given by the safety upper and lower limits and the allowable range in S2.

[0028] 3. Select the best-performing treatment group, extract the corresponding multi-factor time series, construct strong seedling model curves for different crops and seedling ages, and store them in the strong seedling model library.

[0029] S2: Initialization before seedling raising: 1. Install sensors and camera / measuring devices in the tidal seedling greenhouse; 2. Select the target crop and cultivation method in the human-machine interface, and load the corresponding seedling strengthening mode; 3. Set the permissible range for tidal irrigation (maximum / minimum irrigation duration, flooding depth range, nutrient solution EC range, etc.) and the upper and lower safety limits for greenhouse equipment.

[0030] S3: Data Acquisition During Operation: 1. The controller executes tidal irrigation and environmental settings according to the preset initial mode; 2. Periodically collect environmental factors, substrate moisture content, and tidal operation data; 3. Collect seedling images / phenotypic data on a daily or multi-day cycle, and calculate the current seedling vigor index SI_now.

[0031] S4: Calculation of Seedling Strength Index and Environmental Deviation: 1. Based on the seedling age, obtain the target seedling strength index SI_target and the corresponding environmental / substrate reference value for that period from the seedling strength model library; 2. Calculate the seedling strength index deviation ΔSI = SI_now - SI_target; 3. Calculate the environmental and substrate deviation vector ΔEnv (temperature, humidity, light, substrate moisture content, EC, etc.).

[0032] S5: Generation of negative feedback control quantity: 1. Using ΔSI and ΔEnv as inputs, invoke the negative feedback decision module; 2. If ΔSI>0 and the seedlings are growing excessively (taller plants, thinner stems): reduce irrigation frequency or shorten tidal duration, lower nighttime temperature, and appropriately increase light intensity; 3. If ΔSI < 0 and the seedlings are weak (low plant height, small leaf area): appropriately increase the frequency / duration of tides, increase the substrate moisture content and nutrient solution concentration, and optimize temperature and photoperiod; 4. Convert the control results into specific adjustments to tidal irrigation parameters and offsets to environmental setpoints.

[0033] S6: Execution and Cyclic Correction: 1. Control the tidal irrigation actuators and environmental control actuators to operate according to the new parameters; 2. In the next observation period, SI_now is recalculated and compared with the previous period to form a trend judgment (whether the seedling index is steadily converging towards the target range). 3. If ΔSI remains within the threshold for multiple cycles, maintain the current control strategy; otherwise, continue iterative updates.

[0034] S7: End Phase and Mode Output: 1. When the seedlings reach the stage of being ready for transplanting, test whether the seedling vigor index meets the standard for strong seedlings; Output the parameter trajectory of the entire process of tidal irrigation and environmental control for this batch, providing a reference for subsequent seedling cultivation of the same variety and in the same season, and realizing the self-learning and updating of the strong seedling model.

[0035] The above embodiments are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Any modifications, alterations, alterations, or substitutions made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A tidal greenhouse seedling cultivation water, fertilizer, and environmental synergistic control system, characterized in that, include: The system includes an environmental and substrate monitoring module, a seedling phenotypic acquisition device, a data acquisition and preprocessing unit, a negative feedback decision and controller, a tidal irrigation actuator, and an environmental control actuator. The environment and substrate monitoring module and the seedling phenotypic acquisition device are used to collect environmental data, substrate water and fertilizer data and phenotypic data, and upload them to the data acquisition and preprocessing unit. The data acquisition and preprocessing unit outputs the current seedling strength index based on the seedling strength evaluation model, and simultaneously queries the seedling strength model library to obtain the target seedling strength index. The negative feedback decision and controller generates control quantities based on the deviation between the current seedling strength index and the target seedling strength index, as well as the environmental and substrate deviations, and drives the tidal irrigation actuator and the environmental control actuator to achieve coordinated regulation of water, fertilizer and environment.

2. The tidal greenhouse seedling raising water, fertilizer, and environmental synergistic control system according to claim 1, characterized in that, The robust seedling evaluation model is expressed by the following formula: SI = Σ(k=1..K) w_k·PC_k Let the seedling phenotypic index vector be X = [H, D, N, A, W]. T Where H is plant height, D is stem diameter, N is number of leaves, A is leaf area, and W is dry matter content; the i-th index is standardized as follows: z_i = (x_i - μ_i) / σ_i A comprehensive evaluation is established using principal component analysis: the k-th principal component PC_k=Σ(i=1..m) a(k,i)·z_i, where a(k,i) is the loading coefficient; the corresponding eigenvalue is λ_k, and the contribution rate weight w_k = λ_k / Σ(j=1..K) λ_j.

3. The tidal greenhouse seedling raising water, fertilizer, and environmental synergistic control system according to claim 1, characterized in that, The environmental and substrate monitoring module includes an air temperature sensor, a relative humidity sensor, a light intensity sensor, an EC / PH sensor, a tidal bed water level sensor, and a return water flow meter.

4. The tidal greenhouse seedling raising water, fertilizer, and environmental synergistic control system according to claim 1, characterized in that, The seedling phenotypic acquisition device includes a top / side view camera, a depth camera, or a ruler measuring device.

5. The tidal greenhouse seedling raising water, fertilizer, and environmental synergistic control system according to claim 1, characterized in that, The tidal irrigation actuator includes a storage tank, a water pump, a solenoid valve, and inlet and outlet water pipes for the tidal bed, which are used to realize the timed rise and fall of the seedling bed.

6. The tidal greenhouse seedling raising water, fertilizer, and environmental synergistic control system according to claim 1, characterized in that, The environmental control actuators include fans, wet curtains, heating furnaces, and sunshades.

7. A tidal seedling raising method, based on the tidal greenhouse seedling raising water, fertilizer, and environmental synergistic control system according to any one of claims 1-6, characterized in that, include: S1: Construction and database building of the robust seedling model: Seedling cultivation experiments were conducted in an experimental greenhouse with different combinations of environmental factors and substrate moisture content. Plant height, stem diameter, leaf area, and dry matter content were periodically measured. Combined with environmental and substrate data, principal component analysis / factor analysis was used to establish a seedling vigor evaluation model. Define the environment and matrix state vectors: Env_now=[T, RH, L, θ, EC] T Where T is air temperature, RH is relative humidity, L is light intensity, θ is substrate moisture content, and EC is the electrical conductivity of the substrate or nutrient solution; the reference vector is obtained from the robust seedling model library: Env_ref=[T_ref, RH_ref, L_ref, θ_ref, EC_ref] T ; The environment-matrix deviation vector is: ΔEnv = Env_now - Env_ref; The seedling strength index deviation ΔSI and the environment / substrate deviation ΔEnv are combined to form an error vector: e = [ΔSI, ΔEnv] T ] T The control quantity is generated by using a negative feedback control law: Δu = -K·e, where K is the adjustable gain matrix; Map the control input to a control parameter vector: u = [h, τ_flood, τ_int, EC_nut, T_set, RH_set, L_set] T These correspond to the tidal level h, the duration of high tide τ_flood, the irrigation interval τ_int, the nutrient solution EC setting value EC_nut, and the greenhouse temperature, humidity and light setting values, respectively. The parameter update is constrained: u_{k+1} = sat(u_k + Δu, u_min, u_max), where sat(·) represents the saturation constraint on the upper and lower limits; Select the best-performing treatment group, extract the corresponding multi-factor time series, construct strong seedling model curves for different crops and seedling ages, and store them in the strong seedling model library. S2: Initialization before seedling raising: Sensors and camera / measuring devices are deployed in the tidal seedling greenhouse; Select the target crop and cultivation method in the human-computer interface, and load the corresponding seedling strengthening mode; Set permissible limits for tidal irrigation and upper and lower safety limits for greenhouse equipment; S3: Data Acquisition During Operation: The controller executes tidal irrigation and environmental settings according to the preset initial mode; Periodically collect environmental factors, substrate moisture content, and tidal operation data; Collect seedling images / phenotypic data on a daily or multi-day cycle, and calculate the current seedling vigor index SI_now; S4: Calculation of Seedling Strength Index and Environmental Deviation: Based on the seedling age, obtain the target seedling strength index SI_target and the corresponding environmental / substrate reference value for that period from the seedling strength model library; Calculate the seedling strength index deviation ΔSI = SI_now - SI_target; Calculate the environment and matrix deviation vector ΔEnv; S5: Generation of negative feedback control quantity: Using ΔSI and ΔEnv as inputs, the negative feedback decision module is invoked; If ΔSI>0 and seedlings are growing excessively: reduce irrigation frequency or shorten tidal duration, lower nighttime temperature, and increase light intensity; If ΔSI < 0 and the seedlings are weak: increase the frequency / duration of tides, increase the substrate moisture content and nutrient solution concentration; The control results are converted into tidal irrigation parameter adjustment amounts and environmental setpoint offsets. S6: Execution and Cyclic Correction: Control the tidal irrigation actuators and environmental control actuators to operate according to the new parameters; SI_now is recalculated in the next observation period and compared with the previous period to form a trend judgment; If ΔSI remains within the threshold for multiple periods, the current control strategy will be maintained. Otherwise, continue iterative updates; S7: End Phase and Mode Output: When the seedlings reach the stage of being ready for transplanting, test whether the seedling vigor index meets the standard for strong seedlings. Output the parameter trajectory of the entire process of this batch of tidal irrigation and environmental control.

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