Peanut seed efficient germination cultivation method based on improved culture medium

Abstract

The invention relates to the technical field of agricultural intelligent cultivation, and discloses a peanut seed efficient germination cultivation method based on an improved culture medium. The method comprises the following steps: acquiring native state information of peanut seeds in a culture container, wherein the native state information comprises seed coat color, cotyledon plumpness and radicle initial form data; then comparing the information with a pre-stored characteristic spectrum to generate a seed state vector with a differentiation identifier; inputting the vector into a culture medium formula decision network, and outputting a targeted culture medium component adjustment scheme including mineral element ratio, organic substance concentration and gel dosage by the network; and finally, driving an automatic liquid preparation system to perform quantitative mixing and split charging according to the scheme to form a customized solid culture medium. According to the invention, a closed loop from seed state perception to full-automatic preparation of the personalized culture medium is realized, and the precision and efficiency of peanut seed germination cultivation are improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent agricultural cultivation technology, specifically to a method for efficient germination cultivation of peanut seeds based on a modified culture medium. Background Technology

[0002] In peanut germplasm resource preservation, genetic research, and seedling production, seed germination and cultivation are fundamental and crucial steps. Current technologies generally employ universal culture media with fixed compositions for seed cultivation. These methods typically select the culture medium based on the macroscopic classification of peanut varieties, or treat all seeds to be cultivated as a homogeneous population for uniform treatment. The preparation of the culture medium also largely relies on manual experience, involving batch weighing, mixing, and sterilization according to standard formulas, with the operational procedures becoming rigid.

[0003] Existing technologies have shortcomings. Universal culture media cannot respond to the physiological differences between individual peanut seeds from the same or different batches. Using a fixed formula may result in some poorly sized seeds not receiving the necessary nutrients, leading to low germination rates, while high-quality seeds may exhibit excessive growth or deformities due to nutrient overload or inappropriate hormones. Furthermore, the process of manually preparing culture media is susceptible to weighing errors and operational contamination risks, and it is difficult to quickly respond to the need for fine-tuning the formula for different seed conditions, resulting in low efficiency and poor reproducibility. How to accurately identify the native state of individual peanut seeds and dynamically and automatically prepare the most suitable personalized culture medium to improve germination uniformity, robustness, and cultivation efficiency is a problem that needs to be solved in current technology. Summary of the Invention

[0004] The purpose of this invention is to provide a method for efficient germination cultivation of peanut seeds based on a modified culture medium, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides a method for efficient germination cultivation of peanut seeds based on a modified culture medium, the method comprising:

[0006] Acquire the native state information of peanut seed samples in a culture container within a preset time period. The native state information includes at least seed coat color data, cotyledon fullness data, and radicle initial morphology data.

[0007] The original state information is compared item by item with the pre-stored seed feature map, and a seed state vector carrying a differentiated identifier is generated based on the comparison differences.

[0008] The seed state vector is input into the culture medium formulation decision network, which outputs a targeted culture medium component adjustment scheme, including mineral element ratio, organic matter concentration and gelling agent dosage.

[0009] According to the culture medium component adjustment scheme, the automated liquid preparation system is driven to perform quantitative mixing and dispensing operations of the liquid medium to form a customized solid culture medium.

[0010] Preferably, the method further includes:

[0011] Perform environmental parameter initialization on the culture vessel that has been filled with culture medium. The environmental parameter initialization includes setting the temperature gradient, light cycle and gas exchange frequency in the culture space to predetermined values.

[0012] Peanut seed samples that have undergone surface sterilization were implanted onto the surface of the solid culture medium, and continuous monitoring of environmental parameters and culture medium humidity was initiated.

[0013] Collect real-time environmental parameters and culture medium humidity data obtained from monitoring, match them with the preset ideal environment curve for seed germination, and generate an environmental deviation index.

[0014] When the environmental deviation index exceeds the allowable threshold, the environmental control device is activated, and the environmental control device performs compensatory adjustment on at least one physical parameter in the culture space according to the specific value of the environmental deviation index.

[0015] Record time-series data of the entire process from seed implantation to radicle breaking through the seed coat, and capture daily changes in seed morphology during this process to form a seed germination history archive.

[0016] Preferably, the step of comparing the original state information with the pre-stored seed feature map item by item includes:

[0017] The standard feature set corresponding to the current peanut seed variety is retrieved from the seed feature map library. The standard feature set defines the standard color range, standard saturation range and standard radicle morphology of healthy seeds.

[0018] The seed coat color data is quantified by an image analysis unit to obtain a color value, and the color value is compared with the standard color range to calculate the color deviation value.

[0019] The fullness data of the cotyledons is measured by the contour scanning unit to obtain the fullness coefficient, and the fullness coefficient is compared with the standard fullness range to calculate the fullness difference coefficient.

[0020] The initial morphological data of the radicle is analyzed by a microscopic imaging unit to obtain a radicle morphology descriptor. The radicle morphology descriptor is then matched with the standard radicle morphology to generate a morphological difference score.

[0021] The color deviation value, the fullness difference coefficient, and the morphological difference score are aggregated to form the seed state vector.

[0022] Preferably, inputting the seed state vector into the culture medium formulation decision network includes:

[0023] The components in the seed state vector are analyzed, and the color deviation value, the fullness difference coefficient and the morphological difference score are mapped to intensity signals of the demand for specific components in the culture medium.

[0024] Based on the intensity signal, a preset component response rule library is queried. The component response rule library defines the correspondence between different intensity signals and the nitrogen content, phosphorus content, potassium content, sucrose concentration, and plant growth regulator concentration in the culture medium.

[0025] Based on the aforementioned correspondence, a preliminary list of culture medium components is generated;

[0026] Based on the actual types and concentrations of the chemical reagents currently in stock, the preliminary list of culture medium components is verified for feasibility and adjusted for suitability, and finally solidified into an executable adjustment plan for the culture medium components.

[0027] Preferably, the step of driving the automated dispensing system to perform quantitative mixing and dispensing of the liquid medium according to the culture medium component adjustment scheme includes:

[0028] The culture medium component adjustment scheme is converted into a machine-recognizable operation instruction sequence, which precisely controls the valve opening and closing duration of multiple storage tanks and the rotation speed of the peristaltic pump;

[0029] According to the sequence of operating instructions, the automated liquid preparation system sequentially draws up a specified volume of mother liquor and stirs and blends it in a mixing container to form a homogeneous liquid culture medium.

[0030] The liquid culture medium is mixed with the heated and melted gel under incubation conditions, and then quantitatively dispensed into a series of sterile culture containers through a dispensing arm, and left to cool and solidify to form the solid culture medium.

[0031] Preferably, the initialization of environmental parameters for the culture vessel that has been filled with culture medium includes:

[0032] Multiple culture containers holding the solid culture medium are placed on the shelf of a programmable environmental control box;

[0033] The ideal environment curve for seed germination is loaded into the control system of the environmental control box. The curve specifies the target temperature, target light intensity and duration, and target gas circulation rate that should be maintained inside the environmental control box at different stages of germination.

[0034] The control system sets initial parameters according to the curve, drives the cooling and heating module, the LED array and the circulating fan to start working, so that the environment inside the box reaches the predetermined value.

[0035] Preferably, the process of collecting and monitoring real-time environmental parameters and culture medium humidity data, and matching them with a preset ideal environment curve for seed germination, includes:

[0036] Temperature, humidity, light intensity, and culture medium moisture content data are continuously collected by a sensor array distributed within the environmental control box, forming a real-time monitoring data stream;

[0037] Extract the theoretical environmental parameter values ​​corresponding to the current moment from the ideal seed germination environment curve;

[0038] Calculate the differences between real-time temperature data and theoretical temperature value, real-time humidity data and theoretical humidity value, real-time light intensity data and theoretical light intensity value, and real-time culture medium moisture content data and theoretical moisture content value, respectively.

[0039] The weighted sum of each difference is used to calculate the comprehensive environmental deviation index.

[0040] Preferably, the activation of the environmental control device, based on the specific value of the environmental deviation index, includes compensatory adjustment of at least one physical parameter within the cultivation space, comprising:

[0041] The environmental deviation index is input into the proportional-integral-derivative controller;

[0042] The proportional-integral-derivative controller outputs control signal strength for the temperature regulation module, humidification and dehumidification module, or supplemental lighting module based on the magnitude and trend of the environmental deviation index.

[0043] Based on the strength of the control signal, the power of the temperature regulation module, the atomization amount of the humidification and dehumidification module, or the brightness of the supplementary lighting module are increased or decreased accordingly to achieve closed-loop feedback regulation of the physical parameters in the culture space.

[0044] Preferably, the recording of time-series data from seed implantation to radicle breaking through the seed coat, and the capture of daily changes in seed morphology during this process, includes:

[0045] A timed imaging device is fixedly installed above the culture container. The timed imaging device is triggered at a fixed time every day to collect high-definition top view and side view images of the seed samples in the culture container.

[0046] Add a timestamp and culture container number identifier to each acquired image, and store them in chronological order;

[0047] At the same time, the exact moment when the radicle becomes visible, as well as the total time elapsed from seed implantation to that moment, are recorded as germination cycle data;

[0048] All images corresponding to the same culture container number are associated with and encapsulated with the germination cycle data to form the seed germination history archive for that sample.

[0049] Preferably, the method further includes post-processing analysis of the seed germination history archive:

[0050] Image analysis was performed on the daily image sequences in the seed germination history archive to quantify the changes in radicle length, hypocotyl curvature, and cotyledon unfolding area.

[0051] The change curves are time-aligned with the real-time monitoring data stream to analyze the correlation between environmental parameter fluctuations and key events in seed morphology changes;

[0052] Based on the correlation analysis results, the specific parameter settings in the ideal environment curve for seed germination are fine-tuned and optimized to generate an updated version of the environment curve for use in subsequent batches of seed germination cultivation.

[0053] Compared with the prior art, the beneficial effects of the present invention are:

[0054] By acquiring native state information including seed coat color, cotyledon fullness, and initial radicle morphology, and comparing it with pre-stored feature maps to generate a seed state vector, this vector accurately quantifies individual differences and physiological characteristics of seeds. This vector is then input into a culture medium formulation decision network, which analyzes the complex nonlinear relationships between the features of each dimension of the vector and nutrient requirements, thereby dynamically outputting adjustment schemes including precise mineral element ratios, optimal organic matter concentrations, and appropriate gelling agent dosages. This achieves a shift in culture medium formulation from a "general approach" oriented towards varieties to a "one-seed-one-policy" approach oriented towards the real-time state of individual seeds, ensuring that each seed or a homogeneous seed group receives nutritional support strictly matched to its developmental stage and intrinsic potential, overcoming the blindness of fixed formulations.

[0055] Based on the digital adjustment scheme output by the decision network, the automated liquid preparation system is driven to perform quantitative mixing and dispensing of liquid media. This system directly receives and parses formulation instructions, precisely controlling the dosage and mixing sequence of various mother liquors or raw materials to ultimately form a solid culture medium completely consistent with the formulation. The customized formulations generated by intelligent decision-making are transformed into physical culture substrates without loss or deviation, eliminating the errors and contamination risks introduced by manual operation. It ensures that even for a large number of seed samples in varying states, multiple different customized culture media can be prepared efficiently and in parallel, achieving large-scale and standardized operation of personalized culture processes. Attached Figure Description

[0056] Figure 1 This is a schematic diagram illustrating the working principle of the high-efficiency peanut seed germination cultivation method based on modified culture medium described in this invention.

[0057] Figure 2 A flowchart illustrating the workings of a culture medium formulation decision network;

[0058] Figure 3 A flowchart for automated solution preparation and dispensing;

[0059] Figure 4 A combined graph showing the deviation of environmental parameters at different stages of peanut seed germination;

[0060] Figure 5 This is a biaxial line graph showing the changes in morphological indicators during peanut seed germination. Detailed Implementation

[0061] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0062] Please see Figure 1 This invention provides a method for efficient germination cultivation of peanut seeds based on a modified culture medium. The method includes: acquiring the original state information of peanut seed samples in a culture container within a preset time period, wherein the original state information includes at least seed coat color data, cotyledon fullness data, and initial radicle morphology data; comparing the original state information with a pre-stored seed feature map item by item, and generating a seed state vector carrying a differentiated identifier based on the differences generated by the comparison; inputting the seed state vector into a preset culture medium formulation decision network, which outputs a targeted culture medium component adjustment scheme through internal calculations, specifically including parameters such as mineral element ratio, organic matter concentration, and gelling agent dosage; and driving an automated liquid preparation system to perform quantitative mixing and dispensing operations of the liquid medium according to the culture medium component adjustment scheme output by the culture medium formulation decision network, thereby preparing a customized solid culture medium.

[0063] Example 1: See Figure 2In the process of generating the seed state vector, a standard feature set completely corresponding to the peanut seed variety to be cultivated is retrieved from a pre-built seed feature map library. This standard feature set clearly defines the standard color range, standard saturation interval, and standard radicle morphology that a healthy seed should possess. The acquired seed coat color data is quantified and analyzed by an image analysis unit to obtain a numerical value representing the color. This color value is compared with the standard color range defined in the standard feature set to calculate the color deviation value. The cotyledon saturation data is measured by a contour scanning unit to obtain a saturation coefficient. This saturation coefficient is compared with the standard saturation interval defined in the standard feature set to calculate the saturation difference coefficient. The initial radicle morphology data is analyzed by a microscopic imaging unit to obtain a set of radicle morphology descriptors. Similarity matching is performed between these radicle morphology descriptors and the standard radicle morphology defined in the standard feature set to generate a morphological difference score. The calculated color deviation value, saturation difference coefficient, and morphological difference score are aggregated and combined to form the seed state vector. After the seed state vector is input into the culture medium formulation decision network, the network analyzes each component in the vector, mapping the color deviation value, saturation difference coefficient, and morphological difference score to intensity signals indicating the demand for specific components in the culture medium. Based on the intensity signals generated by the mapping, a preset component response rule library is queried. This library defines the correspondence between different intensity signals and the nitrogen, phosphorus, potassium, sucrose, and plant growth regulator concentrations in the culture medium. Based on the queried correspondences, a preliminary list of culture medium components is generated. Subsequently, combined with the actual types and concentrations of currently stocked chemical reagents, the feasibility of this preliminary list of culture medium components is verified and adjusted, ultimately solidifying it into an executable culture medium component adjustment scheme.

[0064] In practical implementation, the efficient peanut seed germination cultivation method based on modified culture medium involves the generation of seed state vectors and the decision-making of culture medium formulation. After acquiring the native state information of peanut seed samples in the culture container within a preset time period, the native state information includes seed coat color data, cotyledon fullness data, and initial radicle morphology data. A standard feature set corresponding to the current peanut seed variety is retrieved from the seed feature map library. The standard feature set defines the standard color range, standard fullness interval, and standard radicle morphology of healthy seeds. The seed coat color data is quantified using an image analysis unit to obtain color values, which are then compared with the standard color range defined in the standard feature set to calculate the color deviation value. The cotyledon fullness data is measured using a contour scanning unit to obtain a fullness coefficient, which is then compared with the standard fullness interval defined in the standard feature set to calculate the fullness difference coefficient. The initial radicle morphology data is analyzed using a microscopic imaging unit to obtain a radicle morphology descriptor, which is then matched with the standard radicle morphology defined in the standard feature set to generate a morphological difference score. The color deviation value, saturation difference coefficient, and morphological difference score are aggregated and combined to form a seed state vector.

[0065] In some embodiments, the similarity matching operation employs the following quantification method: the radicle morphology descriptor contains a set of feature point coordinates, and the standard radicle morphology is defined by a set of reference feature point coordinates. Calculating the morphological difference score between the radicle morphology descriptor and the standard radicle morphology involves a spatial comparison of the feature point sets. In a specific implementation, the seed state vector is input into the culture medium formulation decision network. The culture medium formulation decision network parses each component in the seed state vector, mapping the color deviation value, saturation difference coefficient, and morphological difference score to intensity signals indicating the demand for specific components in the culture medium. Based on the intensity signals, a preset component response rule base is queried. The component response rule base defines the correspondence between different intensity signals and the nitrogen, phosphorus, potassium, sucrose, and plant growth regulator concentrations in the culture medium. Based on the queried correspondences, a preliminary list of culture medium components is generated.

[0066] Example 2: See Figure 3When driving the automated dispensing system according to the culture medium component adjustment scheme, the formulation parameters included in the scheme are converted into a machine-recognizable sequence of operating instructions. This sequence precisely controls the opening and closing duration of valves in multiple storage tanks and the rotation speed of the peristaltic pump. Based on the received sequence, the automated dispensing system sequentially draws specified volumes of various mother liquors from the corresponding storage tanks and thoroughly mixes them in a mixing container to form a homogeneous liquid culture medium. This liquid culture medium is then mixed with a preheated and melted gelling agent under insulated conditions. The mixture is then quantitatively dispensed into a series of sterile culture containers via a dispensing arm, and allowed to cool and solidify to form the solid culture medium.

[0067] In practice, the automated dispensing system performs quantitative mixing and dispensing of liquid media based on the culture medium component adjustment scheme. The scheme is converted into a machine-readable sequence of operating instructions, which precisely controls the opening and closing duration of valves in multiple storage tanks and the rotation speed of peristaltic pumps. These instructions are sent as digital signals to the central controller of the automated dispensing system. After parsing the instructions, the central controller sends pulse control signals to the solenoid valves of the designated storage tanks and the peristaltic pump motors in the corresponding pipelines. According to the received instructions, the automated dispensing system sequentially draws specified volumes of various mother liquors from the corresponding storage tanks. The peristaltic pump's operating time and speed are directly set by the parameters in the instructions to ensure the accuracy of the drawn volume. The drawn mother liquors are transported in a closed pipeline and stirred and blended in a shared mixing container until a homogeneous liquid culture medium is formed.

[0068] In some embodiments, a calculated relationship exists between the valve opening / closing time and the volume of mother liquor to be drawn. For each component of the mother liquor to be drawn, the sequence of operating instructions includes an opening time parameter, which is calculated based on the target volume, the pipe inner diameter, and the calibrated flow rate of the peristaltic pump. The calculation formula can be expressed as:

[0069]

[0070] Where: symbol The symbol represents the opening duration of the valve and peristaltic pump controlling the j-th type of mother liquor pipeline. The symbol represents the volume of the j-th type of stock solution required in the culture medium component adjustment scheme. This represents the stable delivery velocity of the peristaltic pump in the corresponding pipeline per unit time.

[0071] In practice, the pre-mixed liquid culture medium is mixed with a pre-heated and melted gel under insulated conditions. This insulated condition is achieved using a mixing tank with a heating jacket. The mixing process continues until the gel is completely dissolved and evenly dispersed. Then, a sterile dispensing arm quantitatively dispenses the homogeneous mixture of culture medium and gel into a series of sterile culture containers. The dispensing volume for each dispensing operation is controlled by a dispensing subroutine in the operational instruction sequence. After dispensing, the culture containers are transferred to a flat surface to allow the contents to cool and solidify into a solid culture medium. It can be understood that the operational instruction sequence serves as a bridge between the digital culture medium formulation and the physical dispensing action. The generation of the operational instruction sequence depends entirely on the name, target concentration, and final required volume of each chemical component listed in the culture medium component adjustment plan.

[0072] Example 3: After completing the culture medium infusion, environmental parameters were initialized for the culture containers. Multiple culture containers carrying solid culture medium were placed on shelves inside a programmable environmental control box. A preset ideal seed germination environment curve was loaded into the control system of the environmental control box. This curve specifies the target temperature, target light intensity and duration, and target gas circulation rate to be maintained inside the environmental control box at different stages of seed germination. Based on the settings of the ideal seed germination environment curve, the control system loaded the initial parameters and started the cooling and heating module, LED array, and circulating fan to ensure the environmental parameters inside the box reached the predetermined values. Peanut seed samples that had undergone surface sterilization were implanted onto the surface of the solid culture medium, and continuous monitoring of environmental parameters and culture medium humidity was initiated.

[0073] In practice, environmental parameters are initialized for the culture containers that have been filled with culture medium. Multiple culture containers carrying solid culture medium are placed on shelves in a programmable environmental control box. The shelf design allows for uniform airflow between the containers. The ideal seed germination environment curve is loaded into the control system of the programmable environmental control box. This curve, with time as the independent variable, specifies the target temperature, target light intensity and duration, and target gas circulation rate to be maintained inside the box at different stages of peanut seed germination. Based on the loaded ideal seed germination environment curve, the control system sets the initial operating parameters for the cooling and heating module, LED array, and circulating fan, and drives these components to operate. Sensor feedback ensures that the environmental parameters inside the box reach the predetermined values ​​specified at the initial moment of the ideal seed germination environment curve.

[0074] In some embodiments, loading and parsing the ideal environment curve for seed germination involves processing a time function. For the initial parameter settings, the control system needs to read coordinate values ​​from the curve. The target temperature, target light intensity, and target gas circulation rate at the initial moment are transmitted as setpoints to the corresponding control modules. The setpoints are compared with the actual environmental values ​​read by the sensors, and the difference is used to generate initial control commands. The control commands drive the actuators to move until the difference approaches zero, at which point the environment inside the chamber reaches the predetermined value.

[0075] In practice, surface-sterilized peanut seed samples are implanted onto the surface of a solid culture medium. Surface sterilization is performed using standard aseptic procedures. Continuous monitoring of environmental parameters and culture medium humidity is initiated. Environmental parameter monitoring is achieved through multiple sets of sensors deployed at different locations within the programmable environmental control box, while culture medium humidity monitoring is achieved through a moisture content probe inserted at a specific depth into the solid culture medium. Monitoring data is transmitted in real time to the data recording unit of the control system.

[0076] It is understandable that environmental parameter initialization is a process of establishing a baseline state. This initialization ensures that, at the initial moment of peanut seed sample implantation, the temperature gradient, light cycle, and gas exchange frequency within the cultivation space are at the starting point defined by the ideal seed germination environment curve. This baseline state is a prerequisite for subsequent real-time monitoring and matching calculations. In practice, the parameter settings defined in the ideal seed germination environment curve, such as the target gas circulation rate, are initialized based on the speed adjustment of the circulating fan. The control system calculates the required initial circulating fan speed based on the target gas circulation rate. The calculation relationship can be expressed as:

[0077]

[0078] Where: symbol Represents the initial speed setting of the circulating fan, symbol The target gas circulation rate, defined at the initial moment, represents the ideal environment curve for seed germination. (Symbol: ...) This represents a proportionality coefficient that converts the gas circulation rate into the fan speed; the proportionality coefficient is obtained through equipment calibration.

[0079] In some embodiments, the programmable environmental control box has a multi-layered shelf structure. To ensure a uniform environment for each culture container, the environmental parameter initialization process includes a short-term environmental homogenization phase within the box. During the homogenization phase, the cooling and heating modules, LED array, and circulating fan operate at high power for a period of time to stabilize the sensor readings at various points within the box within the allowable fluctuation range of the target predetermined value. Only then does the system switch to normal maintenance mode and prepare to receive peanut seed sample implantation. Optionally, after environmental parameter initialization is complete but before peanut seed sample implantation, the control system generates an initialization completion report. This report lists the current measured values ​​of all environmental parameters and compares them with the set values ​​of the ideal environment curve for seed germination. After confirming that all parameters are within tolerance, the operator performs the peanut seed sample implantation operation and officially starts continuous monitoring. It can be understood that initiating continuous environmental parameter monitoring and culture medium humidity monitoring means that the data acquisition system enters a high-frequency sampling and recording state. The collected environmental parameter and culture medium humidity data constitute the raw data stream for subsequent matching calculations and generation of environmental deviation indicators.

[0080] See Figure 4 This is a composite graph showing the deviation of environmental parameters at different stages of peanut seed germination. Key stage fluctuations: During the water absorption stage (1 day), the deviations in light and gas circulation are significantly higher than in other stages, causing the overall deviation to reach its peak (approximately 4.6%). Control effect: After the germination stage (2 days), the deviations of each parameter decrease significantly, indicating that the compensation adjustment of the environmental control device effectively reduced the deviations. This graph is used to evaluate the control effect of the peanut seed germination environment: By tracking the changes in deviation at each stage, the rationality of the environmental control strategy can be determined, providing data support for optimizing the ideal environment curve for seed germination.

[0081] Example 4: Temperature, humidity, light intensity, and culture medium moisture content data are continuously collected by a sensor array distributed at different locations within the programmable environmental control box, forming a real-time monitoring data stream. Theoretical environmental parameter values ​​corresponding to the current monitoring time are extracted from the ideal seed germination environment curve. The differences between the real-time collected temperature data and the theoretical temperature value, the real-time humidity data and the theoretical humidity value, the real-time light intensity data and the theoretical light intensity value, and the real-time culture medium moisture content data and the theoretical moisture content value are calculated respectively. The calculated differences are weighted and summed to calculate a comprehensive environmental deviation index. When the environmental deviation index exceeds the allowable threshold, the environmental control device is activated. The calculated environmental deviation index is input to a proportional-integral-derivative (PID) controller. Based on the specific value and trend of the environmental deviation index, the PID controller outputs control signal strengths for the temperature adjustment module, humidification / dehumidification module, or supplemental lighting module. Based on the strength of the control signal, the power of the temperature regulation module, the atomization amount of the humidification and dehumidification module, or the brightness of the supplementary lighting module are increased or decreased accordingly to achieve closed-loop feedback regulation of relevant physical parameters in the culture space.

[0082] In practice, real-time environmental parameters and culture medium humidity data are collected and matched with a preset ideal environment curve for seed germination. Temperature, humidity, light intensity, and culture medium moisture content data are continuously collected by a sensor array distributed within the environmental control box, forming a real-time monitoring data stream. At a specific monitoring point in a cultivation batch, a set of real-time monitoring data collected by the system is compared with the corresponding theoretical environmental parameter values ​​extracted from the ideal environment curve for seed germination, as shown in Table 1.

[0083] Table 1: Comparison of Real-time Monitoring Data and Theoretical Environmental Parameter Values

[0084] Parameter type Real-time monitoring value Theoretical value Difference Temperature (degrees Celsius) 24.8 25.0 -0.2 humidity(%) 72.5 75.0 -2.5 Light intensity 98.0 100.0 -2.0 Culture medium moisture content (%) 65.3 66.0 -0.7

[0085] After extracting the theoretical environmental parameter values ​​corresponding to the current moment from the ideal seed germination environment curve, the differences between real-time temperature data and theoretical temperature value, real-time humidity data and theoretical humidity value, real-time light intensity data and theoretical light intensity value, and real-time culture medium moisture content data and theoretical moisture content value are calculated respectively. The weighted sum of each difference is then used to calculate the comprehensive environmental deviation index. The formula for calculating the environmental deviation index is expressed as:

[0086]

[0087] Where: symbol The calculated environmental deviation index is represented by the symbol. Represents the difference between real-time temperature data and theoretical temperature value, with the sign... Represents the difference between real-time humidity data and theoretical humidity value, with the sign... The value represents the difference between real-time illumination intensity data and theoretical illumination intensity value, with the sign... The value represents the difference between the real-time moisture content data and the theoretical moisture content value of the culture medium, with the symbol […]. ,symbol ,symbol ,symbol These represent the preset weighting coefficients corresponding to temperature, humidity, light intensity, and moisture content of the culture medium, respectively.

[0088] In practical implementation, when the calculated environmental deviation index When the preset tolerance threshold is exceeded, the system activates the environmental control device. The environmental deviation index... The input is fed into a proportional-integral-derivative (PID) controller, which then adjusts the input based on the environmental deviation index. The specific numerical values ​​and trends of the output signal determine the control signal strength for the temperature regulation module, humidification / dehumidification module, or supplemental lighting module. Based on the control signal strength output by the proportional-integral-derivative controller, the power of the temperature regulation module, the atomization amount of the humidification / dehumidification module, or the brightness of the supplemental lighting module are correspondingly increased or decreased to achieve closed-loop feedback regulation of the physical parameters within the culture space.

[0089] It is understandable that the input to the proportional-integral-derivative (PID) controller is the environmental deviation index. The difference between the allowable threshold and the control signal strength is the output of the proportional-integral-derivative (PID) controller, used to correct deviations in environmental parameters. The magnitude and direction of this control signal determine the control signal strength. This control signal strength is either an analog or digital quantity, which directly drives the action of actuators such as heaters, compressors, humidifiers, dehumidifiers, or LEDs. In some embodiments, the allowable threshold itself can be a dynamically changing value, adjusted according to the rate of change of parameters defined in the ideal seed germination environment curve. During periods when environmental parameters need to change rapidly, the system appropriately loosens the allowable threshold to reduce unnecessary frequent adjustments; during periods when environmental parameters need to remain stable, the system tightens the allowable threshold to maintain higher environmental stability.

[0090] In practical implementation, compensatory adjustments to physical parameters based on control signal strength manifest as specific equipment actions. For example, when the control signal strength indicates a need for increased temperature, the heating element power in the temperature control module will increase proportionally, while the refrigeration compressor will operate at reduced speed or stop. When the control signal strength indicates a need for increased humidity, the ultrasonic atomizer in the humidification / dehumidification module will activate and operate at a specific frequency, diffusing water mist into the cultivation space. When the control signal strength indicates a need for increased illumination, the LED array in the supplemental lighting module will increase its drive current, thereby increasing output brightness. Optionally, the control parameters of the proportional-integral-derivative (PID) controller—namely, the proportional gain, integral time constant, and derivative time constant—can be pre-calibrated during system initialization based on different environmental control box models and sensor characteristics. The pre-calibration process is completed by applying a step disturbance to the system and observing its adjustment response to obtain optimal control performance.

[0091] Example 5: A timed imaging device is fixedly installed above the culture container. This device is triggered at a fixed time each day to acquire high-resolution top-view and side-view images of the seed samples in the culture container. Each acquired image is timestamped and identified by the culture container number, and stored chronologically. The exact moment when the radicle breaks through the seed coat and becomes visible, as well as the total time elapsed from seed implantation to that moment, are recorded simultaneously as germination cycle data. All image sequences corresponding to the same culture container number are associated and encapsulated with the germination cycle data to form a seed germination history archive for that sample. Post-processing analysis is performed on the seed germination history archive, and image analysis is conducted on the daily image sequences in the archive to quantify the changes in radicle length, hypocotyl curvature, and cotyledon unfolding area. The quantified change curves are time-aligned with the real-time monitoring data stream obtained from environmental monitoring to analyze the correlation between environmental parameter fluctuations and key events in seed morphology changes. Based on the correlation analysis results, the specific parameter settings in the ideal seed germination environment curve are fine-tuned and optimized to generate an updated version of the environmental curve. This updated version of the environmental curve is used in subsequent batches of seed germination cultivation.

[0092] In practice, time-series data is recorded for the entire process from seed implantation to radicle emergence from the seed coat, capturing daily changes in seed morphology. A timed imaging device is fixedly installed above the culture container, triggered at a fixed time each day to acquire high-resolution top-down and side-view images of the seed samples. The trigger signal for the timed imaging device is issued by the time program module of the central control system, which ensures that daily image acquisition occurs at the same time within the light cycle to reduce image quality differences caused by variations in light conditions. Each acquired image is stamped with a timestamp and a culture container number. The timestamp records the year, month, day, hour, minute, and second of acquisition, while the culture container number is written into the image file's metadata along with the image data and stored chronologically in a designated database or storage directory. Simultaneously, the exact time when the radicle becomes visible, and the total duration from seed implantation to the exact time when the radicle becomes visible, are recorded as germination cycle data. The exact time when the radicle becomes visible is either manually confirmed and entered into the system, or automatically identified and recorded by the system using image analysis algorithms. All image sequences corresponding to the same culture container number are associated with and encapsulated with germination cycle data. The image sequence, timestamp, culture container number identifier, and germination cycle data are integrated into a structured data package to form the seed germination history archive of the sample.

[0093] In some embodiments, the timed imaging device includes two independent imaging units: one imaging unit captures high-resolution top-view images vertically downwards, and the other imaging unit captures high-resolution side-view images horizontally. The acquisition actions of the two imaging units are synchronously controlled by the same trigger signal, ensuring that paired top-view and side-view images are obtained simultaneously for the same culture container. These paired images provide multi-angle morphological information for subsequent quantitative analysis. It can be understood that a seed germination history archive is a complete, timestamped record of morphological development. The seed germination history archive not only contains visual images but also key germination cycle data, which is an important temporal indicator for measuring germination efficiency.

[0094] In practice, post-processing analysis is performed on the seed germination history archive. Daily image sequences within the archive are analyzed to quantify the changes in radicle length, hypocotyl curvature, and cotyledon unfolding area. Radicle length is quantified by measuring the pixel distance from the radicle tip to the seed outline reference point in a high-resolution side view image and multiplying it by a calibration coefficient. Hypocotyl curvature is quantified by defining the hypocotyl centerline in the high-resolution side view image and calculating the angle or curvature of the centerline relative to the vertical reference line. Cotyledon unfolding area is quantified by extracting the cotyledon region from the high-resolution top view image using image segmentation techniques and calculating its pixel area. These daily quantified values ​​are concatenated chronologically to form curves showing changes in radicle length, hypocotyl curvature, and cotyledon unfolding area.

[0095] In some embodiments, the hypocotyl curvature is calculated using an image coordinate-based method. In a high-resolution side view image, a set of feature points are manually or automatically selected along the hypocotyl, and a curve representing the hypocotyl centerline is obtained by fitting these feature points. The average angle difference between this fitted curve and the vertical reference line in the image coordinate system is calculated as a measure of the hypocotyl curvature. Specifically, the calculation can be expressed as follows:

[0096]

[0097] Where: symbol Represents the calculated bending angle of the hypocotyl, with the symbol... Represents the number of feature points selected, symbol and symbols This represents the pixel difference between the i-th feature point and the (i+1)-th feature point in the horizontal and vertical coordinate directions of the image.

[0098] In practice, the curves showing changes in radicle length, hypocotyl curvature, and cotyledon unfolding area are time-aligned with the real-time monitoring data stream. The real-time monitoring data stream includes temperature, humidity, light intensity, and culture medium moisture content data. Time alignment synchronizes the time coordinates of the morphological change curves with the time coordinates of the real-time monitoring data stream, ensuring that each morphological data point corresponds to the environmental parameter value at the same moment. The correlation between environmental parameter fluctuations and key events in seed morphological changes is analyzed. Key events include the first appearance of the radicle, significant hypocotyl curvature, and complete cotyledon unfolding. Correlation analysis uses statistical methods to calculate the correlation coefficient between a sequence of environmental parameters and a sequence of morphological index changes within a specific time window. It can be understood that time alignment is a prerequisite for correlation analysis; it ensures a strict correspondence between environmental and morphological data on the time axis, making it possible to analyze whether environmental fluctuations are statistically related to morphological changes.

[0099] In practice, based on the results of correlation analysis, specific parameter settings in the ideal seed germination environment curve are fine-tuned and optimized to generate an updated version of the environment curve. For example, correlation analysis may show that in the early stage of radicle elongation, a slightly higher medium moisture content than the original curve is positively correlated with faster radicle elongation. Based on this finding, the theoretical value of the medium moisture content at the corresponding stage in the ideal seed germination environment curve can be fine-tuned to generate an updated version of the environment curve with a slightly different moisture content setting. The updated version of the environment curve will serve as a new control benchmark for subsequent batches of seed germination cultivation. Optionally, the fine-tuning and optimization process follows the principle of iterative improvement, limiting the modification range of the ideal seed germination environment curve to a preset small range to avoid introducing new instabilities due to excessively large single adjustments. After the updated version of the environment curve is applied to subsequent batches, the seed germination history files generated during the cultivation process will be collected and analyzed again to evaluate the optimization effect and guide possible further adjustments.

[0100] See Figure 5 This is a biaxial line graph showing the changes in morphological indicators during peanut seed germination. The trends of the three morphological indicators are radicle length, cotyledon unfolding area, and hypocotyl curvature. Hypocotyl curvature (blue) increases rapidly in the early germination stage (0-4 days) and then slows down; cotyledon unfolding area (green) enters a rapid growth phase in the middle germination stage (4-8 days); radicle length (red) grows slowly overall, reaching only about 22 mm at 10 days. The rapid growth period of hypocotyl curvature overlaps with the initiation period of cotyledon unfolding, reflecting the synergistic nature of morphological changes during seed germination. This graph is used for dynamic monitoring of peanut seed germination morphology: by tracking the rate of change of different morphological indicators, the health of seed germination can be assessed, providing morphological basis for optimizing culture medium formulations or environmental parameters.

[0101] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for efficient germination of peanut seeds based on modified medium, characterized in that, The method comprises: acquiring the original state information of the peanut seed sample in the culture container within a preset time period, the original state information at least including seed coat color data, cotyledon fullness data, and radicle initial morphology data; comparing the original state information with the pre-stored seed characteristic atlas item by item, and generating a seed state vector carrying a differentiated identifier according to the comparison difference; inputting the seed state vector into a culture medium formula decision network, the culture medium formula decision network outputting a targeted culture medium component adjustment scheme, the culture medium component adjustment scheme including mineral element ratio, organic matter concentration, and gel agent dosage; driving an automatic liquid preparation system to perform quantitative mixing and dispensing of liquid media according to the culture medium component adjustment scheme, to form a customized solid culture medium.

2. The improved medium based high efficient germination method of peanut seed according to claim 1, characterized in that, The method further comprises: performing environment parameter initialization on the culture container that has completed medium infusion, the environment parameter initialization including setting the temperature gradient, light period, and gas exchange frequency in the culture space to predetermined values; implanting the peanut seed sample that has undergone surface disinfection treatment into the surface of the solid culture medium, and starting continuous environment parameter monitoring and culture medium humidity monitoring; collecting the monitored real-time environment parameters and culture medium humidity data, matching them with a preset ideal seed germination environment curve, and generating an environment deviation index; when the environment deviation index exceeds the allowable threshold, activating an environment control device, the environment control device compensating at least one physical parameter in the culture space according to the specific value of the environment deviation index; recording the time sequence data from seed implantation to radicle breakthrough of the seed coat, and capturing daily change images of the seed morphology during the process, to form a seed germination history archive.

3. The improved medium based high efficient germination method of peanut seed according to claim 1, characterized in that, The comparison of the original state information with the pre-stored seed characteristic atlas item by item comprises: calling a standard characteristic set corresponding to the current peanut seed variety from the seed characteristic atlas library, the standard characteristic set defining the standard color range, standard fullness interval, and standard radicle morphology of healthy seeds; quantifying the seed coat color data through an image analysis unit to obtain a color value, and comparing the color value with the standard color range to calculate a color deviation value; measuring the cotyledon fullness data through a contour scanning unit to obtain a fullness coefficient, and comparing the fullness coefficient with the standard fullness interval to calculate a fullness difference coefficient; analyzing the radicle initial morphology data through a microscopic imaging unit to obtain a radicle morphology descriptor, and performing similarity matching of the radicle morphology descriptor with the standard radicle morphology to generate a morphology difference score; aggregating the color deviation value, the fullness difference coefficient, and the morphology difference score to form the seed state vector.

4. The improved medium based high efficient germination method of peanut seed according to claim 3, characterized in that, The inputting of the seed state vector into the culture medium formula decision network comprises: analyzing each component in the seed state vector, and mapping the color deviation value, the fullness difference coefficient, and the morphology difference score into intensity signals of the demand for specific components in the culture medium, respectively; According to the intensity signal, a preset component response rule base is queried, and the component response rule base defines a corresponding relationship between different intensity signals and nitrogen element content, phosphorus element content, potassium element content, sucrose concentration and plant growth regulator concentration in the culture medium; According to the corresponding relationship, a preliminary culture medium component list is generated; In combination with actual types and concentrations of chemical reagents in current inventory, the preliminary culture medium component list is subjected to feasibility verification and adaptive adjustment, and finally solidified into an executable culture medium component adjustment scheme.

5. The improved medium based high efficient germination and raising method of peanut seed according to claim 3, characterized in that, The driving of the automatic liquid preparation system to perform quantitative mixing and dispensing of liquid medium according to the culture medium component adjustment scheme comprises: The culture medium component adjustment scheme is converted into a machine-recognizable operation instruction sequence, which accurately controls the opening and closing time of the valve of the multiple liquid storage tanks and the rotation speed of the peristaltic pump; According to the operation instruction sequence, the automatic liquid preparation system sequentially sucks a specified volume of mother liquor and stirs and fuses in a mixing container to form a uniform liquid medium; The liquid medium is mixed with a heated and melted gel under a heat preservation condition, and then quantitatively filled into a series of sterile culture containers through a dispensing arm, and waits for cooling and solidification to form the solid culture medium.

6. The improved medium based high efficient germination and raising method of peanut seeds according to claim 2, characterized in that, The initialization of the environmental parameters of the culture container into which the culture medium has been filled comprises: Placing multiple culture containers carrying the solid culture medium on the shelves of a programmable environmental control box; Loading the ideal seed germination environment curve into the control system of the environmental control box, which specifies the target temperature value, target light intensity and duration, and target gas circulation rate that should be maintained in the environmental control box during different germination stages; The control system sets initial parameters according to the curve to drive the refrigeration and heating module, light-emitting diode array and circulating fan to start working to make the environment in the box reach the predetermined value.

7. The improved medium based high efficient germination method of peanut seed according to claim 6, characterized in that, The matching calculation of the collected real-time environmental parameters and culture medium humidity data with the preset ideal seed germination environment curve comprises: Continuous acquisition of temperature data, humidity data, light intensity data and culture medium water content data by a sensor array distributed in the environmental control box to form a real-time monitoring data stream; Extracting the theoretical environmental parameter value corresponding to the current time from the ideal seed germination environment curve; Respectively calculating the difference between the real-time temperature data and the theoretical temperature value, the difference between the real-time humidity data and the theoretical humidity value, the difference between the real-time light intensity data and the theoretical light intensity value, and the difference between the real-time culture medium water content data and the theoretical water content value; Weighted sum of each difference value to calculate the comprehensive environmental deviation index.

8. The improved medium based high efficient germination method of peanut seed according to claim 7, characterized in that, The activation of the environmental regulation device to compensate for at least one physical parameter in the culture space according to the specific value of the environmental deviation index comprises: Inputting the environmental deviation index into a proportional-integral-derivative controller; The proportional-integral-derivative controller outputs control signal strength for the temperature regulation module, the humidification and dehumidification module or the light supplementing module according to the size and change trend of the environmental deviation index. According to the control signal strength, the power of the temperature adjustment module, the atomization amount of the humidifying and dehumidifying module or the brightness of the light supplementing module are enhanced or weakened correspondingly, so as to realize closed-loop feedback adjustment of the physical parameters in the culture space.

9. The improved medium based high efficient germination method of peanut seed according to claim 8, characterized in that, The time sequence data from the seed implantation to the radicle breaking through the seed coat is recorded, and the daily change image of the seed morphology in the process is captured, including: A timing photographing device is fixedly installed above the culture container, which is triggered at a fixed time every day to collect high-definition overhead and side-view images of the seed sample in the culture container; A time stamp and a culture container number identifier are added to each collected image, and the images are stored in chronological order; At the same time, the exact time when the radicle is visible is recorded, and the total length of time from the seed implantation to the time is recorded as the germination cycle data; All images corresponding to the same culture container number are associated and packaged with the germination cycle data to form the seed germination history file of the sample.

10. The improved medium based high efficient germination method of peanut seed according to claim 8, characterized in that, The method further includes post-processing analysis of the seed germination history file: Image analysis is performed on the daily image sequence in the seed germination history file to quantify the change curves of radicle length, hypocotyl bending degree and cotyledon expansion area; The change curves are time-aligned with the real-time monitoring data stream to analyze the correlation between environmental parameter fluctuations and key events of seed morphology changes; According to the correlation analysis result, the specific parameter set value in the ideal seed germination environment curve is fine-tuned and optimized to generate an updated version of the environment curve, which is used for the seed germination cultivation process of subsequent batches.

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