Method for automatically sterilizing solanaceae seeds based on hygrometric dynamic regulation

Abstract

The application discloses a solanaceae family seed automatic disinfection working method based on dynamic adjustment of humidity and heat, relates to the technical field of seed automatic disinfection, and is used for solving the problem that precise regulation and control based on physiological state is difficult to realize, and the probability of disease occurrence is increased. The seed coat state and conductivity of solanaceae family seeds after disinfection are detected, the proportion of a highlighted area is calculated, and the ethanol concentration is collected. The humidity response characteristics are analyzed through the proportion of the highlighted area and the ethanol concentration. The number of cracked seeds is counted, and the temperature response characteristics are analyzed in combination with the conductivity. Whether a ventilation processing mechanism is started is comprehensively judged. After ventilation, a regulation and control time is set. The respiration intensity and the tray water film thickness are monitored in real time. The humidity and heat states are classified according to the respiration change trend and the water film thickness. Cooling or drying channels are selected according to the classification results. The dynamic monitoring and regulation and control of the humidity and heat states after disinfection are realized. The ventilation channels are automatically selected through multi-dimensional sensing. The disinfection environment is optimized. The seed quality and storage stability are effectively improved.

Description

Technical Field

[0001] This invention relates to the field of automatic seed disinfection technology, and more specifically, to an automatic disinfection method for Solanaceae seeds based on dynamic humidity and heat regulation. Background Technology

[0002] For Solanaceae crops (such as tomatoes, eggplants, and peppers), seed disinfection is a crucial step in the seedling stage to ensure seed health and prevent the spread of diseases. Traditional seed disinfection methods mainly involve soaking seeds in hot water, treating them with chemical agents, or using ozone to kill pathogenic microorganisms attached to the seed surface.

[0003] The existing technology has the following shortcomings:

[0004] Currently, most existing disinfection processes use fixed temperature and humidity conditions, which cannot be adjusted according to the dynamic changes of seeds during the disinfection process. This can easily lead to excessively high temperatures or humidity, thereby damaging seed activity. It is difficult to achieve precise control based on physiological state, and there is a lack of dynamic humidity and heat regulation methods based on seed state. This cannot effectively solve the problem of decreased seed activity and the risk of mold growth caused by uneven temperature and humidity during disinfection, resulting in reduced germination rate and increased probability of disease. Therefore, an automatic disinfection method for Solanaceae seeds based on dynamic humidity and heat regulation is proposed.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide an automatic disinfection method for Solanaceae seeds based on dynamic regulation of humidity and heat. By utilizing real-time monitoring and analysis of seed physiological indicators such as seed coat condition, electrical conductivity, proportion of bright areas, ethanol release concentration, and respiration intensity, combined with a comprehensive judgment of humidity and temperature sensing characteristics, dynamic regulation of ventilation, cooling, or drying channels is achieved to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an automatic disinfection method for Solanaceae seeds based on dynamic humidity and heat regulation, comprising the following steps:

[0008] Step S1: Detect the seed coat condition and electrical conductivity of Solanaceae seeds after disinfection, calculate the proportion of bright areas using the seed coat condition, and collect the ethanol concentration released by Solanaceae seeds;

[0009] Step S2: Analyze humidity sensing characteristics using the proportion of bright areas and ethanol concentration, count the number of Solanaceae seeds with cracks, analyze temperature sensing characteristics using conductivity, and determine whether to enter the ventilation treatment mechanism by combining humidity sensing characteristics and temperature sensing characteristics.

[0010] Step S3: After entering the ventilation treatment mechanism, set the control time and monitor the respiration intensity of the solanaceous seeds and the thickness of the water film on the solanaceous seed tray in real time during the control time.

[0011] Step S4: Calculate the respiratory change trend based on the respiratory intensity, classify the humid and hot state of Solanaceae seeds by combining the respiratory change trend with the water film thickness, and select to enter the cooling channel or the drying channel according to the classification results.

[0012] In a preferred embodiment, in step S1, the seed coat state of the Solanaceae seed after disinfection includes the highlight feature value of the seed coat pixel.

[0013] High-resolution images of Solanaceae seeds were acquired and processed to obtain grayscale images of Solanaceae seeds;

[0014] The median gray value of each pixel in the grayscale image is used as the grayscale reference value.

[0015] If the grayscale value of a pixel in a grayscale image is greater than the grayscale reference value, then the highlight feature value of the seed coat pixel is 1; otherwise, the highlight feature value of the seed coat pixel is 0.

[0016] In a preferred embodiment, in step S1, the equivalent impedance of the Solanaceae seed is obtained by a non-contact capacitively coupled conductivity sensor, and the conductivity of the Solanaceae seed is calculated based on the equivalent impedance.

[0017] The proportion of the highlighted area is calculated based on the highlight feature value of the seed coat pixels of Solanaceae seeds;

[0018] The concentration of ethanol released from Solanaceae seeds was detected using an infrared ethanol sensor.

[0019] In a preferred embodiment, in step S2, the humidity sensing characteristics are obtained by weighting the proportion of the bright area and the concentration of ethanol released by the Solanaceae seeds.

[0020] A deep learning-based crack detection algorithm is used to determine whether cracks exist on grayscale images of Solanaceae seeds and to count the number of Solanaceae seeds with cracks.

[0021] The temperature sensing characteristics were calculated by combining the number of Solanaceae seeds with cracks with the normalized value of the electrical conductivity of Solanaceae seeds.

[0022] In a preferred embodiment, in step S2, the humidity sensing characteristics and temperature sensing characteristics are compared with preset humidity sensing characteristic thresholds and preset temperature sensing characteristic thresholds, respectively, for determination.

[0023] If the humidity sensing characteristic is greater than or equal to the preset humidity sensing characteristic threshold and the temperature sensing characteristic is greater than or equal to the preset temperature sensing characteristic threshold, then the ventilation process is initiated.

[0024] Conversely, the ventilation process will not be initiated.

[0025] In a preferred embodiment, in step S3, the control time is set and divided into multiple collection times. The concentration of carbon dioxide released by the metabolic activity of Solanaceae seeds at the collection time is detected by a carbon dioxide sensor, and the total mass of the current Solanaceae seeds is obtained by a weight sensor set at the bottom of the tray.

[0026] The difference between the carbon dioxide concentration detected at the current sampling time and the carbon dioxide concentration at the previous sampling time is taken as the amount of carbon dioxide released within the sampling time interval.

[0027] The respiration intensity of Solanaceae seeds at the current collection time is calculated by dividing the product of the carbon dioxide release from Solanaceae seeds within the collection time interval by the total mass of Solanaceae seeds within the collection time interval and the control time.

[0028] In a preferred embodiment, in step S3, a laser is emitted by a laser sensor toward a Solanaceae seed tray, and the timestamps of the laser emission and the timestamps of the received reflected laser are recorded by the time sampling unit of the laser sensor.

[0029] The distance from the laser sensor to the water film on the Solanaceae seed tray is calculated based on the timestamp of the emitted laser and the timestamp of the received reflected laser.

[0030] The distance from the laser sensor to the water film on the solanaceous seed tray is calculated by emitting a laser from the laser sensor towards the water film on the solanaceous seed tray.

[0031] The difference between the distance from the laser sensor to the solanaceous seed tray and the distance from the laser sensor to the water film on the solanaceous seed tray is taken as the water film thickness of the solanaceous seed tray.

[0032] In a preferred embodiment, in step S4, the respiration intensity of Solanaceae seeds at adjacent collection times within the control time is subtracted to obtain a respiration change characteristic value, and the respiration change characteristic values ​​are combined into a respiration change characteristic value set.

[0033] The arithmetic mean of each respiratory change characteristic value is used to obtain the respiratory change trend characteristic value;

[0034] If the characteristic value of the respiration change trend is greater than the preset respiration change trend threshold, then the respiration change trend of the Solanaceae seeds is judged to be an upward trend.

[0035] If the characteristic value of the respiration change trend is less than the negative of the preset respiration change trend threshold, then the respiration change trend of Solanaceae seeds is judged to be a downward trend.

[0036] Otherwise, the respiration trend of Solanaceae seeds is judged to be a stable trend.

[0037] In a preferred embodiment, in step S4, if the water film thickness of the Solanaceae seed tray is greater than or equal to the water film thickness threshold, then the Solanaceae seeds are determined to have a high water film thickness.

[0038] Conversely, if the water film thickness is low, it can be determined that the seeds of the Solanaceae family have a low water film thickness.

[0039] The humid and heat status of Solanaceae seeds can be determined by combining the trend of respiration changes with the thickness of the water film in the seed tray.

[0040] If the respiration trend is upward or stable and the water film thickness in the solanaceous seed tray is low, then the solanaceous seeds are determined to be in a high-temperature state.

[0041] If the respiration trend is downward and the water film thickness in the solanaceous seed tray is low, then the solanaceous seeds are considered to be in a normal state.

[0042] When the seeds of the Solanaceae family are in a high-humidity state, they are introduced into the drying channel;

[0043] When the seeds of the Solanaceae family are at a high temperature, they are introduced into a cooling channel;

[0044] When Solanaceae seeds are in a normal state, they should remain in their current state without any adjustment.

[0045] The technical effects and advantages of this invention are as follows:

[0046] This invention detects the seed coat condition and electrical conductivity of Solanaceae seeds after disinfection, calculates the proportion of bright areas based on the seed coat condition, and collects the ethanol concentration released by the seeds. It analyzes humidity sensing characteristics using the proportion of bright areas and ethanol concentration, counts the number of seeds with cracks, and combines electrical conductivity analysis with temperature sensing characteristics. By integrating these humidity and temperature sensing characteristics, it determines whether to activate the ventilation mechanism. Once the ventilation mechanism is activated, a control time is set, and the respiration intensity and tray water film thickness are monitored in real time. The respiration trend is calculated based on the respiration intensity, and the humidity and heat status is classified based on the water film thickness. Based on the classification results, the seed is directed to either a cooling channel or a drying channel. This achieves dynamic monitoring and control of the humidity and heat status of Solanaceae seeds after disinfection. By comprehensively judging the seed condition through multi-dimensional sensing indicators, it automatically selects the appropriate ventilation channel, optimizes the disinfection environment, effectively improves the quality and storage stability of Solanaceae seeds, and reduces the risk of mold and damage. Attached Figure Description

[0047] Figure 1 This is a flowchart illustrating the implementation of the automatic disinfection method for Solanaceae seeds based on dynamic humidity and heat regulation according to the present invention.

[0048] Figure 2 This is a schematic diagram illustrating the steps of the automatic disinfection method for Solanaceae seeds based on dynamic humidity and heat regulation according to the present invention. Detailed Implementation

[0049] 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.

[0050] An automated disinfection method for Solanaceae seeds based on dynamic temperature and humidity regulation, such as Figures 1 to 2 As shown, it includes the following steps:

[0051] Step S1: Detect the seed coat condition and electrical conductivity of Solanaceae seeds after disinfection, calculate the proportion of bright areas using the seed coat condition, and collect the ethanol concentration released by Solanaceae seeds;

[0052] Step S2: Analyze humidity sensing characteristics using the proportion of bright areas and ethanol concentration, count the number of Solanaceae seeds with cracks, analyze temperature sensing characteristics using conductivity, and determine whether to enter the ventilation treatment mechanism by combining humidity sensing characteristics and temperature sensing characteristics.

[0053] Step S3: After entering the ventilation treatment mechanism, set the control time and monitor the respiration intensity of the solanaceous seeds and the thickness of the water film on the solanaceous seed tray in real time during the control time.

[0054] Step S4: Calculate the respiratory change trend based on the respiratory intensity, classify the humid and hot state of Solanaceae seeds by combining the respiratory change trend with the water film thickness, and select to enter the cooling channel or the drying channel based on the classification results.

[0055] The specific implementation is as follows:

[0056] In step S1, the solanaceous seeds are fed into a sterilization pipeline, which is a closed flow pipeline suitable for continuous solanaceous seed treatment. The sterilization pipeline is equipped with a spraying device, which evenly sprays disinfectant onto the surface of the incoming solanaceous seeds, achieving non-contact sterilization of the seeds.

[0057] It should be noted that the disinfectant is not the only option and can be selected according to actual needs, including but not limited to hydrogen peroxide solution, sodium hypochlorite solution, ethanol solution, etc.

[0058] The seed coat condition of Solanaceae seeds after disinfection is a comprehensive description of the physical and visual characteristics of the external structure of Solanaceae seeds after disinfection, including the highlight feature values ​​of the seed coat pixels.

[0059] High-resolution images of Solanaceae seeds are captured using a high-resolution industrial camera.

[0060] The grayscale image of the Solanaceae seed is obtained by processing the high-resolution image of the Solanaceae seed using a grayscale normalization algorithm;

[0061] The median gray value of each pixel in the grayscale image is used as the grayscale reference value.

[0062] If the grayscale value of a pixel in a grayscale image is greater than the grayscale reference value, then the highlight feature value of the seed coat pixel is 1; otherwise, the highlight feature value of the seed coat pixel is 0.

[0063] It should be noted that a high-resolution industrial camera is a device for acquiring high-definition images of the surface of Solanaceae seeds; grayscale normalization algorithm is used to standardize the grayscale values ​​of the acquired Solanaceae seed images, mapping the original grayscale values ​​to a uniform standard range; grayscale value is the brightness of a pixel from black to white, used to represent the numerical value of the brightness intensity of a pixel in the image.

[0064] A non-contact capacitively coupled conductivity sensor is installed in the detection chamber of the disinfection pipeline. The excitation electrode and detection electrode of the non-contact capacitively coupled conductivity sensor form a capacitive coupling path with the Solanaceae seed through the container wall. The alternating current is transmitted to the detection electrode through the conductive channel formed by the water and dissolved ions inside the container wall and the Solanaceae seed. The detection electrode collects the return signal. The control unit synchronously detects and corrects the phase of the collected current signal and the applied voltage signal to obtain the equivalent impedance of the Solanaceae seed. The ratio of the pre-calibrated electrode constant to the equivalent impedance of the Solanaceae seed is used as the conductivity.

[0065] It should be noted that the non-contact capacitively coupled conductivity sensor is a sensor that uses the principle of capacitive coupling to measure conductivity. It includes an excitation electrode, a detection electrode, and a control unit, and is used to obtain the conductivity of Solanaceae seeds. The excitation electrode is the electrode to which an AC signal is applied by the sensor's driving circuit. The detection function is to sense and collect the electrical signal transmitted through the measured object. The control unit is responsible for signal generation, acquisition, processing, and result output. The pre-calibrated electrode constant is a coefficient that reflects the geometric dimensions and electric field distribution characteristics of the electrode structure. It is used to convert the equivalent impedance into conductivity. The pre-calibrated electrode constant is stored in the non-contact capacitively coupled conductivity sensor and is used to convert the equivalent impedance into conductivity during actual detection.

[0066] The proportion of the highlighted area is calculated based on the highlight feature values ​​of the seed coat pixels of Solanaceae seeds. The calculation formula is as follows: ,in, This refers to the number of pixels in the seed coat of a Solanaceae seed. For the first Highlighted feature values ​​of seed coat pixels of a Solanaceae seed This represents the percentage of the highlighted area.

[0067] The highlighted areas correspond to the water film or water-soaked areas formed on the seed coat surface due to moisture absorption, and the proportion of the highlighted areas reflects the degree of moisture on the seed surface.

[0068] The disinfected solanaceous seeds were placed in a sealed collection chamber. A ventilation equilibration time was set to allow the environment to stabilize. A miniature fan was then activated to allow the gas inside the chamber to flow through the infrared ethanol sensor detection area to obtain the concentration of ethanol released by the solanaceous seeds.

[0069] It should be explained that the ventilation equilibrium time refers to the time required for the gas composition inside the sealed collection chamber to reach a stable state after the solanaceous seeds are placed in it, and this time is set by professionals; the miniature fan is a small, low-power wind device used for the circulation of gas inside the sealed collection chamber; the infrared ethanol sensor detection area refers to a specially set sensing area inside the sealed collection chamber used to obtain the concentration of ethanol released by the solanaceous seeds.

[0070] In step S2, under humid and hot conditions, the seed coat absorbs water and swells, altering its surface smoothness and light transmittance, resulting in an increase in bright areas in the image. Simultaneously, under high humidity stress, the seed undergoes anaerobic respiration, releasing ethanol. Based on this theory, the humidity sensing characteristics are calculated after standardizing the proportion of bright areas and the concentration of ethanol released by Solanaceae seeds. The humidity sensing characteristics are as follows: ,in, This is the standardized value of the highlighted area proportion. This represents the standardized value of the ethanol concentration released by Solanaceae seeds. and To preset the weighting coefficients, It is a humidity-sensing feature;

[0071] It should be noted that the standardization methods include, but are not limited to, standard linear transformation based on interval scaling, Z-Score standardization based on statistics, or normalization based on nonlinear mapping functions. The specific methods of standardization will not be elaborated upon here. A larger proportion of the highlighted area indicates more significant water infiltration into the seed coat, resulting in a higher humidity sensing characteristic; conversely, a smaller proportion indicates a lower humidity sensing characteristic. A higher concentration of ethanol released by Solanaceae seeds indicates more active metabolism and enhanced anaerobic respiration, resulting in a higher humidity sensing characteristic; conversely, a lower concentration indicates a lower humidity sensing characteristic. Preset weighting coefficients are used to adjust the influence of the proportion of the highlighted area and the concentration of ethanol released by Solanaceae seeds on the calculation of humidity sensing characteristics. Principal component analysis is performed using a large amount of experimental or monitoring data to obtain the contribution of each factor, and weighting coefficients are determined based on the contribution. Specifically, for the same variety of Solanaceae seeds, multiple batches of disinfection experiments are conducted under various preset temperature and humidity conditions. The proportion of the highlighted area, ethanol concentration, proportion of cracked seeds, and conductivity data for each batch of seeds are recorded, and the final seed activity (such as germination rate) is simultaneously measured as a quality label. Then, using the proportion of bright areas, ethanol concentration, proportion of cracked seeds, and conductivity as raw variables, PCA was used to analyze the contribution of each variable to the differences in seed activity. Variables with greater contribution were assigned a larger weighting coefficient when constructing the comprehensive feature set, thus determining the specific value of the weighting coefficient. For example, in a calibration experiment for tomato seeds, the PCA analysis results showed that the contribution of the proportion of bright areas and ethanol concentration were 0.6 and 0.4, respectively. and The weighting coefficients can be set to 0.6 and 0.4 respectively. The weighting coefficients can be updated by repeating the above calibration experiments according to changes in seed variety, batch, or production environment.

[0072] The deep learning crack detection algorithm is used to determine whether there are cracks in the grayscale image of Solanaceae seeds and to count the number of Solanaceae seeds with cracks.

[0073] It should be noted that the deep learning-based crack detection algorithm uses a trained neural network model to perform pixel-level classification and segmentation of the surface image of Solanaceae seeds to determine whether cracks exist in the seeds.

[0074] The conductivity of Solanaceae seeds was processed using the Max-Min normalization method to obtain normalized values. The normalized values ​​are as follows: ,in, Electrical conductivity of Solanaceae seeds. and These represent the maximum and minimum electrical conductivity values ​​for Solanaceae seeds. This represents the normalized electrical conductivity value of Solanaceae seeds;

[0075] High-temperature stress causes rapid evaporation of internal seed moisture, leading to cracks in the seed coat due to uneven internal and external pressure. Simultaneously, cell membrane damage results in electrolyte leakage, causing increased electrical conductivity. Therefore, the combination of the percentage of cracked seeds and electrical conductivity characterizes the degree of temperature stress experienced by the seed. Based on this theory, the temperature-sensitivity characteristics are calculated by combining the number of cracked Solanaceae seeds with the normalized electrical conductivity of Solanaceae seeds. The calculation formula is as follows: ,in, This represents the number of Solanaceae seeds with cracks. This refers to the number of seeds in the Solanaceae family. This represents the normalized electrical conductivity value of Solanaceae seeds. and To preset the weighting coefficients, It is a temperature-sensing feature;

[0076] It should be noted that the higher the electrical conductivity of Solanaceae seeds, the greater the evaporation of moisture on the surface and inside of the seeds due to high temperatures, and the greater the temperature sensing characteristics. Conversely, the lower the electrical conductivity, the smaller the temperature sensing characteristics. The greater the number of Solanaceae seeds with cracks, the lower the heat insulation ability of the seeds, and the greater the temperature sensing characteristics. Conversely, the smaller the number of cracked seeds, the smaller the temperature sensing characteristics.

[0077] The humidity sensing characteristics and temperature sensing characteristics are compared with preset humidity sensing characteristic thresholds and preset temperature sensing characteristic thresholds, respectively, for judgment.

[0078] If the humidity sensing characteristic is greater than or equal to the preset humidity sensing characteristic threshold and the temperature sensing characteristic is greater than or equal to the preset temperature sensing characteristic threshold, then the ventilation process is initiated.

[0079] Conversely, the ventilation process will not be initiated.

[0080] It should be explained that the Max-Min normalization method is a linear data normalization technique used to normalize the electrical conductivity of Solanaceae seeds. The preset humidity and temperature sensing thresholds are used to determine whether Solanaceae seeds have entered the ventilation treatment mechanism. A large amount of data related to Solanaceae seeds, such as the proportion of bright areas, ethanol concentration, and electrical conductivity, are collected under the same environment through experimental calibration. Combined with seed physiological characteristics, the correlation between different indicators and actual humidity and temperature states is analyzed. Statistical analysis is used to determine the threshold range that can distinguish between normal and abnormal states. The preset weighting coefficients can be set based on historical batch data, experimental calibration data, and real-time monitoring data, as described above using principal component analysis. The ventilation treatment mechanism refers to the process of regulating the humidity and temperature state of the environment surrounding Solanaceae seeds by controlling airflow exchange when abnormal humidity and temperature characteristics are detected. Based on a comprehensive judgment of humidity and temperature sensing characteristics, a fan is driven or airflow is guided to introduce external cold, dry, humid, or warm air into the storage area of ​​Solanaceae seeds, or to exhaust internal air, thereby reducing humidity, lowering temperature, or maintaining a suitable environment to prevent mold growth and preserve the activity of Solanaceae seeds.

[0081] In step S3, the control time is set and divided into multiple collection times, and the concentration of carbon dioxide released by the metabolic activity of Solanaceae seeds at the collection times is detected by a carbon dioxide sensor.

[0082] The total mass of Solanaceae seeds within the controlled time period is obtained by a weight sensor placed at the bottom of the tray.

[0083] The difference between the carbon dioxide concentration released by the metabolic activity of Solanaceae seeds at the current collection time and the carbon dioxide concentration at the previous collection time is taken as the amount of carbon dioxide released by Solanaceae seeds within the collection time interval.

[0084] Divide the carbon dioxide release of Solanaceae seeds within the collection time interval by the product of the collection time interval and the total mass of Solanaceae seeds within the control time period to obtain the respiration intensity of Solanaceae seeds at the current collection time.

[0085] During the control period, a laser is emitted by a laser sensor and directed toward the Solanaceae seed tray. The time stamp of the laser sensor emitting the laser and the time stamp of the received reflected laser are recorded by the time sampling unit of the laser sensor.

[0086] The distance from the laser sensor to the Solanaceae seed tray is obtained by multiplying the difference between the timestamp of receiving the reflected laser and the timestamp of the laser sensor emitting the laser by the laser propagation speed, and then dividing the result by 2.

[0087] A laser sensor emits a laser beam towards the water film on the solanaceous seed tray, and the distance from the laser sensor to the water film on the solanaceous seed tray is determined using the method described above.

[0088] The difference between the distance from the laser sensor to the solanaceous seed tray and the distance from the laser sensor to the water film on the solanaceous seed tray is taken as the water film thickness of the solanaceous seed tray.

[0089] It needs to be explained that the carbon dioxide sensor is a sensor device that detects the concentration of carbon dioxide in the environment in real time through optical or electrochemical principles, and is used to detect the concentration of carbon dioxide released during the metabolism of solanaceous seeds; the control time refers to a fixed period of time used to monitor the respiration intensity of solanaceous seeds and the thickness of the water film in the seed tray in real time after the ventilation treatment mechanism is activated, and is set according to the respiration fluctuation cycle of solanaceous seeds, covering at least one respiration fluctuation cycle; the weight sensor is a device that converts the mass signal into a measurable electrical signal output, and is used to detect the total mass of solanaceous seeds in the seed tray in real time; the laser sensor is a sensor that uses the principle of laser beam emission and reception to measure distance. By emitting a laser beam towards the target object and receiving the reflected light, it calculates the time difference of light propagation to accurately obtain the distance information of the solanaceous seed tray and its water film, and supports real-time detection of water film thickness; the time sampling unit of the laser sensor is the core component for realizing the distance measurement function of the laser sensor, and is used to record the timestamps of laser emission and reception.

[0090] In step S4, the respiratory intensity of Solanaceae seeds at adjacent collection times within the control time is subtracted to obtain respiratory change characteristic values, and the respiratory change characteristic values ​​are combined into a respiratory change characteristic value set.

[0091] The arithmetic mean of each respiratory change characteristic value is used to obtain the respiratory change trend characteristic value;

[0092] Compare the characteristic values ​​of respiratory change trends with the preset threshold values ​​of respiratory change trends:

[0093] If the characteristic value of the respiratory change trend is greater than the preset respiratory change trend threshold, then the respiratory change trend will be an upward trend during the control period.

[0094] If the characteristic value of the respiratory change trend is less than the negative of the preset respiratory change trend threshold, then the respiratory change trend will be downward during the control period.

[0095] If the characteristic value of the respiratory change trend is greater than or equal to the negative of the preset respiratory change trend threshold and the characteristic value of the respiratory change trend is less than or equal to the preset respiratory change trend threshold, then the respiratory change trend is a stable trend within the control period.

[0096] It should be noted that when the respiration trend is upward, the metabolic activity of Solanaceae seeds is enhanced and the ambient temperature rises; when the respiration trend is downward, the metabolic activity of Solanaceae seeds is weakened and the ambient temperature falls.

[0097] The thickness of the water film in the solanaceous seed tray is compared with a water film thickness threshold for determination:

[0098] If the water film thickness in the tray of Solanaceae seeds is greater than or equal to the water film thickness threshold, then the Solanaceae seeds are judged to have a high water film thickness.

[0099] If the water film thickness in the solanaceous seed tray is less than the water film thickness threshold, the solanaceous seeds are judged to have low water film thickness.

[0100] The humid and heat status of Solanaceae seeds can be determined by combining the trend of respiration changes with the thickness of the water film in the seed tray.

[0101] If the water film thickness in the tray for Solanaceae seeds is high, then the trend of respiration changes will not be judged, and the Solanaceae seeds will be determined to be in a high humidity state.

[0102] If the respiration trend is upward or stable and the water film thickness in the solanaceous seed tray is low, then the solanaceous seeds are determined to be in a high-temperature state.

[0103] If the respiration trend is downward and the water film thickness in the solanaceous seed tray is low, then the solanaceous seeds are considered to be in a normal state.

[0104] Determine whether to direct the seeds into a cooling or drying channel based on the classification results of their humid and hot conditions.

[0105] If the seeds of the Solanaceae family are in a high-humidity state, then introduce them into the drying channel;

[0106] If the seeds of the Solanaceae family are in a high-temperature state, they should be introduced into a cooling channel;

[0107] If the seeds of the Solanaceae family are in a normal state, then keep them as they are and no adjustments are needed.

[0108] It should be explained that the preset respiration change trend threshold and water film thickness threshold are important parameters for judging the humid and hot state of Solanaceae seeds. The threshold is dynamically determined based on a machine learning model. A classification model is established, and machine learning algorithms, such as decision trees and support vector machines, are used to train the humid and hot state classification model in conjunction with respiration change trends and water film thickness features. After the model is trained, the optimal threshold range is determined using the model's classification boundary or probability output. When Solanaceae seeds are in a high-humidity state, they are highly susceptible to mold growth and seed decay, requiring the introduction of a drying channel to reduce humidity. When Solanaceae seeds are in a high-temperature state, although the humidity is low, the high temperature will accelerate… Solanaceous seeds undergo metabolism and respiration, leading to a decline in quality. Cooling channels are necessary to lower the temperature. When solanaceous seeds are in a normal state, low temperature and low humidity constitute an ideal storage environment, requiring no additional adjustments and avoiding unnecessary energy consumption and mechanical intervention. Drying channels accelerate the evaporation of water film from the surface of solanaceous seeds through heated air, reducing seed moisture content or controlling the thickness of the water film on the tray to prevent excessive moisture from causing mold, abnormal germination, or storage deterioration. Cooling channels remove heat from the seed surface through low-temperature airflow, lowering seed temperature or controlling localized tray temperature to prevent high temperatures from adversely affecting seed respiration and activity.

[0109] Finally, it should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0110] Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0111] In this document, the singular forms “a,” “an,” and “the” may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that terms such as “comprising / including” or “having” specify the presence of the stated features, integrals, steps, operations, components, parts, or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, integrals, steps, operations, components, parts, or combinations thereof. Meanwhile, the term “and / or” as used in this specification includes any and all combinations of the associated listed items.

[0112] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0113] The above description of the disclosed embodiments will enable those skilled in the art to make or use various modifications to these embodiments. It will be readily apparent to those skilled in the art that the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An automatic disinfection method for Solanaceae seeds based on dynamic humidity and heat regulation, characterized in that: Includes the following steps: Step S1: Detect the seed coat condition and electrical conductivity of Solanaceae seeds after disinfection, calculate the proportion of bright areas using the seed coat condition, and collect the ethanol concentration released by Solanaceae seeds; Step S2: Analyze humidity sensing characteristics using the proportion of bright areas and ethanol concentration, count the number of Solanaceae seeds with cracks, analyze temperature sensing characteristics using conductivity, and determine whether to enter the ventilation treatment mechanism by combining humidity sensing characteristics and temperature sensing characteristics. Step S3: After entering the ventilation treatment mechanism, set the control time and monitor the respiration intensity of the solanaceous seeds and the thickness of the water film on the solanaceous seed tray in real time during the control time. Step S4: Calculate the respiratory change trend based on the respiratory intensity, classify the humid and hot state of Solanaceae seeds by combining the respiratory change trend with the water film thickness, and select to enter the cooling channel or the drying channel according to the classification results.

2. The automatic disinfection method for Solanaceae seeds based on dynamic heat and humidity regulation according to claim 1, characterized in that: In step S1, the seed coat state of the Solanaceae seeds after disinfection includes the highlight feature values ​​of the seed coat pixels of the Solanaceae seeds; High-resolution images of Solanaceae seeds were acquired and processed to obtain grayscale images of Solanaceae seeds; The median gray value of each pixel in the grayscale image is used as the grayscale reference value. If the grayscale value of a pixel in a grayscale image is greater than the grayscale reference value, then the highlight feature value of the seed coat pixel is 1. Conversely, the highlight feature value of the seed coat pixel is 0.

3. The automatic disinfection method for Solanaceae seeds based on dynamic humidity and heat regulation according to claim 2, characterized in that: In step S1, the equivalent impedance of the Solanaceae seed is obtained by a non-contact capacitive coupling conductivity sensor, and the conductivity of the Solanaceae seed is calculated based on the equivalent impedance. The proportion of the highlighted area is calculated based on the highlight feature value of the seed coat pixels of Solanaceae seeds; The concentration of ethanol released from Solanaceae seeds was detected using an infrared ethanol sensor.

4. The automatic disinfection method for Solanaceae seeds based on dynamic humidity and heat regulation according to claim 3, characterized in that: In step S2, the humidity sensing characteristics are obtained by weighting the proportion of the bright area and the concentration of ethanol released by the Solanaceae seeds. A deep learning-based crack detection algorithm is used to determine whether cracks exist on grayscale images of Solanaceae seeds and to count the number of Solanaceae seeds with cracks. The temperature sensing characteristics were calculated by combining the number of Solanaceae seeds with cracks with the normalized value of the electrical conductivity of Solanaceae seeds.

5. The automatic disinfection method for Solanaceae seeds based on dynamic humidity and heat regulation according to claim 4, characterized in that: In step S2, the humidity sensing characteristics and temperature sensing characteristics are compared with preset humidity sensing characteristic thresholds and preset temperature sensing characteristic thresholds, respectively, for judgment. If the humidity sensing characteristic is greater than or equal to the preset humidity sensing characteristic threshold and the temperature sensing characteristic is greater than or equal to the preset temperature sensing characteristic threshold, then the ventilation process is initiated. Conversely, the ventilation process will not be initiated.

6. The automatic disinfection method for Solanaceae seeds based on dynamic heat and humidity regulation according to claim 1, characterized in that: In step S3, the control time is set and divided into multiple collection times. The carbon dioxide concentration released by the metabolic activity of Solanaceae seeds at the collection time is detected by a carbon dioxide sensor, and the total mass of Solanaceae seeds at the current time is obtained by a weight sensor set at the bottom of the tray. The difference between the carbon dioxide concentration detected at the current sampling time and the carbon dioxide concentration at the previous sampling time is taken as the amount of carbon dioxide released within the sampling time interval. The respiration intensity of Solanaceae seeds at the current collection time is calculated by dividing the product of the carbon dioxide release from Solanaceae seeds within the collection time interval by the total mass of Solanaceae seeds within the collection time interval and the control time.

7. The automatic disinfection method for Solanaceae seeds based on dynamic humidity and heat regulation according to claim 1, characterized in that: In step S3, a laser is emitted from a laser sensor and directed toward a Solanaceae seed tray, and the timestamps of the laser emission and the received reflected laser are recorded by the time sampling unit of the laser sensor. The distance from the laser sensor to the water film on the Solanaceae seed tray is calculated based on the timestamp of the emitted laser and the timestamp of the received reflected laser. The distance from the laser sensor to the water film on the solanaceous seed tray can be calculated by emitting a laser beam through the laser sensor. The difference between the distance from the laser sensor to the solanaceous seed tray and the distance from the laser sensor to the water film on the solanaceous seed tray is taken as the water film thickness of the solanaceous seed tray.

8. The automatic disinfection method for Solanaceae seeds based on dynamic humidity and heat regulation according to claim 1, characterized in that: In step S4, the respiratory intensity of Solanaceae seeds at adjacent collection times within the control time is subtracted to obtain respiratory change characteristic values, and the respiratory change characteristic values ​​are combined into a respiratory change characteristic value set. The arithmetic mean of each respiratory change characteristic value is calculated to obtain the respiratory change trend characteristic value; If the characteristic value of the respiration change trend is greater than the preset respiration change trend threshold, then the respiration change trend of the Solanaceae seeds is judged to be an upward trend. If the characteristic value of the respiration change trend is less than the negative of the preset respiration change trend threshold, then the respiration change trend of Solanaceae seeds is judged to be a downward trend. Otherwise, the respiration trend of Solanaceae seeds is judged to be a stable trend.

9. The automatic disinfection method for Solanaceae seeds based on dynamic heat and humidity regulation according to claim 1, characterized in that: In step S4, if the water film thickness of the Solanaceae seed tray is greater than or equal to the water film thickness threshold, the Solanaceae seeds are determined to have a high water film thickness. Conversely, if the water film thickness is low, it can be determined that the seeds of the Solanaceae family have a low water film thickness. The humid and heat status of Solanaceae seeds can be determined by combining the trend of respiration changes with the thickness of the water film in the seed tray. If the respiration trend is upward or stable and the water film thickness in the solanaceous seed tray is low, then the solanaceous seeds are determined to be in a high-temperature state. If the respiration trend is downward and the water film thickness in the solanaceous seed tray is low, then the solanaceous seeds are considered to be in a normal state. When the seeds of the Solanaceae family are in a high-humidity state, they are introduced into the drying channel; When the seeds of the Solanaceae family are at a high temperature, they are introduced into a cooling channel; When Solanaceae seeds are in a normal state, they should remain in their current state without any adjustment.

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