A fruit and vegetable product purification system based on quality assessment

Abstract

This application relates to the field of computer technology, and in particular to a fruit and vegetable product purification system based on quality assessment. The system includes a multi-dimensional quality perception module, an intelligent decision-making module, a purification execution module, and a post-purification quality verification module. The multi-dimensional quality perception module collects multi-dimensional quality parameters of fruits and vegetables in real time and generates quality feature vectors. The intelligent decision-making module, based on the quality feature vectors, calls a pre-set expert rule base and combines it with a pre-trained reinforcement learning model to generate purification control commands. The purification execution module drives the various technical purification units to start operation after the fruits and vegetables enter the corresponding purification chamber according to the chamber matching command. The post-purification quality verification module detects the pollutant removal effect and the fruit and vegetable quality retention rate after purification, and classifies the fruits and vegetables into qualified products, products awaiting re-inspection, and unqualified products based on the test results. This application helps to achieve precise fruit and vegetable purification.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a purification and treatment system for fruit and vegetable products based on quality assessment. Background Technology

[0002] As consumers' demands for food safety and quality continue to rise, the rationality and precision of fruit and vegetable purification processes are becoming increasingly important as a crucial step in ensuring food safety and extending shelf life. However, existing fruit and vegetable purification systems generally suffer from the following technical shortcomings: traditional purification systems often adopt a one-size-fits-all, fixed processing mode, pre-setting uniform parameters such as washing time and purification intensity, completely ignoring the individual differences of fruit and vegetable varieties, leading to incomplete removal of contaminants or damage to fruit and vegetable quality; they rely solely on manual sorting or single-dimensional visual screening, failing to obtain information such as the internal quality of fruits and vegetables; and they rely heavily on single physical cleaning or chemical disinfection, unable to flexibly adjust technical solutions for different types of contamination.

[0003] Therefore, there is an urgent need for a precise and intelligent purification system for fruits and vegetables to address the technical challenges of traditional purification systems. Summary of the Invention

[0004] Therefore, it is necessary to provide a fruit and vegetable product purification system based on quality assessment that can achieve precise purification of fruits and vegetables, addressing the aforementioned technical problems.

[0005] In the first aspect, this application provides a purification system for fruit and vegetable products based on quality assessment. The system includes a multi-dimensional quality perception module, an intelligent decision-making module, a purification execution module, and a post-purification quality verification module. The multi-dimensional quality perception module is used to collect multi-dimensional quality parameters of fruits and vegetables in real time, generate quality feature vectors, and transmit the quality feature vectors to the intelligent decision-making module. The intelligent decision-making module is used to call a pre-set expert rule base based on the quality feature vector, combine it with a pre-trained reinforcement learning model, generate purification control instructions, and transmit the purification control instructions to the purification execution module. The purification control instructions include purification technology combination schemes, operating parameters of each purification technology unit, and cabin matching instructions. The purification execution module is used to drive each technical purification unit to start operation according to the purification control command after the fruits and vegetables enter the corresponding purification chamber according to the chamber matching command. The purification quality verification module is used to detect the pollutant removal effect and the fruit and vegetable quality retention rate after the fruits and vegetables have been purified, and to classify the fruits and vegetables into qualified products, products awaiting re-inspection, and unqualified products based on the test results.

[0006] In one embodiment, the multi-dimensional quality perception module includes a visual perception unit, a texture characteristic perception unit, and a safety risk perception unit. The visual perception unit is used to acquire the shape and color features of fruits and vegetables through a high-resolution color camera and multispectral / hyperspectral imaging components, identify internal defects and component distribution of fruits and vegetables, and non-destructively detect the soluble solids content, total acidity and sugar-acid ratio of fruits and vegetables through a partial least squares regression model. The texture characteristic sensing unit is used to evaluate the hardness and elastic texture parameters of fruits and vegetables online using a non-contact acoustic vibration sensor or an optical coherence tomography detector. The safety risk perception unit is used to monitor volatile organic compounds in fruits and vegetables, provide early warning of microbial contamination risk levels, and quickly screen for elemental pollutants.

[0007] In one embodiment, the fruit and vegetable product purification system based on quality assessment further includes a data processing module, which is communicatively connected to the multi-dimensional quality perception module. The data processing module is used to acquire the multi-dimensional quality parameters of fruits and vegetables collected by the multi-dimensional quality perception module, perform filtering, noise reduction and normalization processing on the multi-dimensional quality parameters of fruits and vegetables, remove outliers, and feed back the processed multi-dimensional quality parameters of fruits and vegetables to the multi-dimensional quality perception module.

[0008] In one embodiment, the fruit and vegetable product purification system based on quality assessment further includes an external quality screening module, which is located at the front end of the multi-dimensional quality perception module. The external quality screening module is used to collect images of the appearance of fruits and vegetables, analyze the morphological integrity and surface condition of fruits and vegetables through image recognition algorithms, identify unqualified fruits and vegetables that are severely rotten, deformed, or have surface damage areas exceeding a preset threshold, and trigger the sorting execution mechanism to automatically remove the unqualified fruits and vegetables from the processing flow.

[0009] In one embodiment, the technical purification unit includes a chemical purification unit, a physical purification unit, and a novel technology unit, each of which operates independently or collaboratively according to the purification technology combination scheme. The chemical purification unit includes a hydroxyl water ion generating module and an ozone water treatment module. The hydroxyl water ion generating module is equipped with an adjustable electrolysis power supply. By adjusting the electrolysis current, the generation rate of hydroxyl free radicals is controlled to specifically degrade pollutants on the surface and shallow layers of fruits and vegetables. The ozone water treatment module is used to efficiently kill pathogenic microorganisms on the surface of fruits and vegetables by controlling the ozone concentration and reaction time. The physical purification unit includes an ultrasonic cleaning module and a microbubble and vortex water flow module. The ultrasonic cleaning module is equipped with a variable frequency drive circuit. By adjusting the output power and working frequency, it performs differentiated physical peeling and cleaning for fruits and vegetables with different textures. The microbubble and vortex water flow module consists of a variable pump, a microbubble generator, and a flow guiding component. By adjusting the pump speed, the intensity of the vortex water flow is changed, and the gas-liquid mixing ratio is controlled to generate microbubbles of different particle sizes, realizing flexible switching between gentle cleaning and powerful decontamination to adapt to fruits and vegetables with different tolerance levels. The novel technology unit is used to generate reactive oxygen and nitrogen species and ultraviolet light through a plasma generator, so as to achieve non-thermal sterilization and pesticide residue degradation without the need to add chemical reagents.

[0010] In one embodiment, the purification execution module is further configured to monitor the operating parameters of each technical purification unit in real time through an online sensor network, and to feed back the monitored operating parameters to the intelligent decision-making module in real time; The intelligent decision-making module compares the real-time operating parameters fed back with the preset purification parameter thresholds, and fine-tunes the operating parameters of each technical purification unit based on the comparison results, forming a closed-loop control.

[0011] In one embodiment, the intelligent decision-making module has a built-in parameter deviation warning mechanism. When the real-time operating parameters fed back by the purification execution module exceed the purification parameter threshold for a preset duration, a local audible and visual warning is triggered.

[0012] In one embodiment, the post-purification quality verification module includes a purification effect monitoring unit, a quality retention monitoring unit, and a sorting unit; The purification effect monitoring unit is used to detect the pesticide residue degradation rate, microbial kill rate and heavy metal residue, and to verify whether the corresponding preset threshold has been reached. The quality retention monitoring unit is used to retest the nutrient content, hardness, and surface color changes of fruits and vegetables, and to calculate the nutrient loss rate and hardness retention rate. The sorting unit is used to classify fruits and vegetables into qualified products, products awaiting re-inspection, and unqualified products based on the test results.

[0013] In one embodiment, the fruit and vegetable product purification system based on quality assessment further includes a cloud-based digital optimization module, which includes a data storage unit, a model optimization unit, and a traceability management unit. The data storage unit is used to store multi-dimensional quality parameters, purification control instructions, operating parameters of each technical purification unit, and test results for each batch of fruits and vegetables, forming a traceable database for the entire chain. The model optimization unit is used to dynamically update the expert rule base and reinforcement learning model parameters through reinforcement learning algorithms; The traceability management unit is used to generate a unique traceability QR code for each batch of qualified products.

[0014] In one embodiment, the fruit and vegetable product purification system based on quality assessment further includes a data communication module, which adopts a multi-mode communication architecture to realize real-time data transmission between modules.

[0015] In summary, this application includes the following beneficial technical effects: By collecting multi-dimensional quality parameters in real time through a multi-dimensional quality perception module, the limitations of single-dimensional detection can be avoided, providing reliable data support for accurate decision-making. The intelligent decision-making module generates corresponding purification control instructions based on quality feature vectors, which can be specifically adapted to fruits and vegetables with different quality states, abandoning the one-size-fits-all approach and achieving precise purification. The purification execution module, through chamber matching and instruction execution, ensures that fruits and vegetables with different purification needs are processed in their dedicated scenarios, avoiding problems such as incomplete purification or damage to fruits and vegetables caused by incorrect activation of technical purification units or incorrect parameters. The post-purification quality verification module detects the pollutant removal effect and the fruit and vegetable quality retention rate, which can screen out qualified products and provide feedback for subsequent optimization of purification parameters, further improving the level of precision. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of a fruit and vegetable product purification system based on quality assessment in one embodiment. Figure 2 This is a schematic diagram of a fruit and vegetable product purification system based on quality assessment in another embodiment. Detailed Implementation

[0017] This invention provides a purification system for fruit and vegetable products based on quality assessment.

[0018] The embodiments of the present invention will now be described in more detail with reference to the accompanying drawings. While some embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the accompanying drawings and embodiments are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0019] In the description of the embodiments disclosed in this invention, the term "comprising" and similar terms should be understood as open-ended inclusion, i.e., "including but not limited to". The term "based on" should be understood as "at least partially based on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first", "second", etc., may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0020] For ease of understanding, the specific process of the embodiments of the present invention is described below. Please refer to [link / reference]. Figure 1 One embodiment of the fruit and vegetable product purification system based on quality assessment in this invention includes: a multi-dimensional quality perception module, an intelligent decision-making module, a purification execution module, and a post-purification quality verification module. The multi-dimensional quality perception module is used to collect multi-dimensional quality parameters of fruits and vegetables in real time, generate quality feature vectors, and transmit the quality feature vectors to the intelligent decision-making module. The intelligent decision-making module is used to generate purification control instructions based on the quality feature vector, call the pre-set expert rule base, combine the pre-trained reinforcement learning model, and transmit the purification control instructions to the purification execution module. The purification control instructions include purification technology combination scheme, operating parameters of each technology purification unit, and cabin matching instructions. The purification execution module is used to drive each technical purification unit to start operation according to the purification control instructions after the fruits and vegetables enter the corresponding purification chamber according to the chamber matching instructions; The post-purification quality verification module is used to detect the pollutant removal effect and the fruit and vegetable quality retention rate after the fruits and vegetables have been purified. Based on the test results, the fruits and vegetables are classified into qualified products, products awaiting re-inspection, and unqualified products.

[0021] Specifically, this system mainly consists of a multi-dimensional quality perception module, an intelligent decision-making module, a purification execution module, and a post-purification quality verification module. The multi-dimensional quality perception module is responsible for the core task of comprehensively collecting fruit and vegetable quality data. It can capture parameters of fruits and vegetables in multiple dimensions, such as external morphology, internal composition, and texture characteristics, in real time. Through data integration and standardization, it generates quality feature vectors containing key information such as fruit and vegetable variety characteristics, maturity level, and hardness value. This vector is then transmitted to the intelligent decision-making module, providing a comprehensive and reliable data foundation for subsequent purification decisions. The intelligent decision-making module is the control core of the system. After receiving the quality feature vector, it first calls a pre-set expert rule base. This rule base is built based on a large amount of agricultural and food scientific research data and practical application experience, covering the basic processing logic corresponding to different fruit and vegetable types and quality states. Simultaneously, it combines a pre-trained reinforcement learning model to generate customized purification control instructions, including purification technology combination schemes, operating parameters of each purification unit (such as power, time, and concentration), and chamber matching instructions, and transmits these instructions to the purification execution module. The purification execution module is the carrier for precise purification. Once fruits and vegetables enter the corresponding purification chamber according to instructions, the module drives the various technical purification units to start in an orderly manner, operating independently or collaboratively according to a preset technical combination scheme. The post-purification quality verification module serves as the system's quality control point. After the fruits and vegetables have completed purification, it initiates comprehensive testing. On one hand, it tests the effectiveness of pollutant removal, including safety indicators such as pesticide residue degradation rate, pathogenic microorganism kill rate, and heavy metal residue levels. On the other hand, it assesses the retention of fruit and vegetable quality, including quality indicators such as nutrient content, firmness, and surface color changes. Finally, based on the test results, the fruits and vegetables are clearly classified as qualified, awaiting re-inspection, or unqualified.

[0022] In one embodiment, the multi-dimensional quality perception module includes a visual perception unit, a texture characteristic perception unit, and a safety risk perception unit. The visual perception unit is used to acquire the shape and color characteristics of fruits and vegetables through a high-resolution color camera and multispectral / hyperspectral imaging components, identify internal defects and component distribution of fruits and vegetables, and non-destructively detect the soluble solids content, total acidity, and sugar-acid ratio of fruits and vegetables through a partial least squares regression model. The texture characteristic perception unit is used to evaluate the hardness and elasticity parameters of fruits and vegetables online through a non-contact acoustic vibration sensor or optical coherence tomography (OCT) scanner. The safety risk perception unit is used to monitor volatile organic compounds in fruits and vegetables, provide early warning of microbial contamination risk levels, and quickly screen for elemental pollutants.

[0023] Specifically, such as Figure 2As shown, the multi-dimensional quality perception module includes a visual perception unit, a texture characteristic perception unit, and a safety risk perception unit. The visual perception unit is equipped with a high-resolution color camera and a multispectral / hyperspectral imaging component. The high-resolution color camera can accurately capture the shape and color characteristics of fruits and vegetables and identify visible defects such as surface lesions and mechanical damage. The multispectral / hyperspectral imaging component can penetrate the skin of fruits and vegetables to identify internal defects and component distribution that are not visible to the naked eye, such as browning and water core. At the same time, this unit integrates a partial least squares regression model, which can non-destructively detect soluble solids content (related to sweetness), total acidity (related to taste), and sugar-acid ratio based on spectral data, obtaining core flavor indicators without damaging the fruits and vegetables. The texture characteristic sensing unit employs non-contact detection technology, avoiding damage to fruits and vegetables caused by traditional puncture testing. It captures the acoustic response of fruits and vegetables after slight vibrations using a non-contact acoustic vibration sensor, or analyzes the internal structural density of fruits and vegetables using an optical coherence tomography (OCT) scanner. Both methods allow for online assessment of key texture parameters such as hardness and elasticity, quantifying the processing resistance of fruits and vegetables. For example, harder root vegetables can withstand stronger physical cleaning, while less elastic berries require gentler processing. The safety risk sensing unit focuses on potential safety hazards in fruits and vegetables. By monitoring volatile organic compounds, it provides early warnings of microbial contamination risk levels, and rapidly screens for elemental pollutants such as heavy metals, providing a comprehensive understanding of the safety status of fruits and vegetables.

[0024] In one embodiment, the fruit and vegetable product purification system based on quality assessment further includes a data processing module, which is communicatively connected to the multi-dimensional quality perception module. The data processing module is used to acquire the multi-dimensional quality parameters of fruits and vegetables collected by the multi-dimensional quality perception module, filter, reduce noise, and normalize the multi-dimensional quality parameters of fruits and vegetables, remove outliers, and feed back the processed multi-dimensional quality parameters of fruits and vegetables to the multi-dimensional quality perception module.

[0025] Specifically, the data processing module first acquires the raw quality parameters collected by the multi-dimensional quality perception module in real time. These parameters come from different sensors and may have issues such as noise interference, numerical drift, and outliers. For example, spectral data may fluctuate due to ambient light, and texture detection data may show abnormal peaks due to the angle at which the vegetables are placed. To address these issues, the module sequentially performs filtering (removing high-frequency noise), noise reduction (smoothing data fluctuations), and normalization (unifying parameter scales and eliminating the influence of dimensions). Simultaneously, an outlier identification algorithm removes interfering data that exceeds a reasonable range, ensuring data stability and reliability. The processed multi-dimensional quality parameters of fruits and vegetables are fed back to the multi-dimensional quality perception module in real time, providing direct support for the module to generate quality feature vectors with a unified structure and reliable accuracy.

[0026] In one embodiment, the fruit and vegetable product purification and treatment system based on quality assessment also includes an external quality screening module, which is set in front of the multi-dimensional quality perception module. The external quality screening module is used to collect images of the appearance of fruits and vegetables, analyze the morphological integrity and surface condition of fruits and vegetables through image recognition algorithms, identify unqualified fruits and vegetables that are severely rotten, deformed, or have surface damage areas exceeding a preset threshold, and trigger the sorting execution mechanism to automatically remove unqualified fruits and vegetables from the processing flow.

[0027] Specifically, the external quality screening module is positioned in front of the multi-dimensional quality perception module. Its core function is to preemptively remove obviously substandard fruits and vegetables, reducing waste of subsequent processing resources and improving overall processing efficiency. The module captures real-time images of the fruits and vegetables' appearance using a high-resolution image acquisition component. Then, it utilizes a deep learning-based image recognition algorithm to analyze the fruit and vegetable status from two dimensions: first, morphological integrity, identifying deformed or severely deformed fruits and vegetables. These not only have low value but may also lead to insufficient subsequent purification due to their irregular shape; second, surface condition, identifying severely rotten fruits and vegetables with surface damage exceeding a preset threshold. These fruits and vegetables may carry a large number of pathogenic microorganisms, easily contaminating other fruits and vegetables, and the damaged areas are prone to juice loss and quality deterioration during purification. When substandard fruits and vegetables are identified, the module immediately triggers a sorting mechanism (such as a sorting conveyor belt) to quickly remove them from the processing flow and direct them into a dedicated recycling channel.

[0028] In one embodiment, the technical purification unit includes a chemical purification unit, a physical purification unit, and a novel technology unit. Each technical purification unit operates independently or collaboratively according to the purification technology combination scheme. The chemical purification unit includes a hydroxyl water ion generating module and an ozone water treatment module. The hydroxyl water ion generating module is equipped with an adjustable electrolysis power supply, which controls the generation rate of hydroxyl free radicals by adjusting the electrolysis current to specifically degrade pollutants on the surface and shallow layers of fruits and vegetables. The ozone water treatment module is used to efficiently kill pathogenic microorganisms on the surface of fruits and vegetables by controlling the ozone concentration and reaction time. The physical purification unit includes an ultrasonic cleaning module and microbubbles and vortex water flow. The ultrasonic cleaning module is equipped with a variable frequency drive circuit. By adjusting the output power and working frequency, it performs differentiated physical peeling and cleaning for fruits and vegetables with different textures. The microbubble and vortex water flow module consists of a variable pump, a microbubble generator, and a flow guiding component. By adjusting the pump speed, the intensity of the vortex water flow is changed, and the gas-liquid mixing ratio is controlled to generate microbubbles of different particle sizes, realizing flexible switching between gentle cleaning and powerful decontamination to adapt to fruits and vegetables with different tolerance levels. The new technology unit is used to generate active oxygen and nitrogen species and ultraviolet light through a plasma generator to achieve non-thermal sterilization and pesticide residue degradation without the addition of chemical reagents.

[0029] Specifically, the technical purification unit adopts a modular and reconfigurable design. Through the flexible combination of chemical purification units, physical purification units, and new technology units, it adapts to the purification needs of different types of fruits and vegetables and their pollution states, achieving precise adaptation of one solution for each type of fruit and vegetable. The chemical purification unit focuses on the efficient degradation and sterilization of pollutants and consists of a hydroxyl water ion generation module and an ozone water treatment module. The hydroxyl water ion generation module is equipped with an adjustable electrolysis power supply, which precisely controls the generation rate of hydroxyl free radicals by adjusting the electrolysis current. Hydroxyl free radicals have extremely strong oxidizing power and can specifically degrade difficult-to-remove pesticide residues such as organophosphates and carbamates on the surface and shallow layers of fruits and vegetables, leaving no chemical residue after the reaction. The ozone water treatment module achieves precise control of ozone concentration and action time through a high-precision ozone generator and flow control valve, which can efficiently kill pathogenic microorganisms such as Salmonella and E. coli. At the same time, ozone is easily decomposed into oxygen, which will not cause secondary pollution to fruits and vegetables. The physical purification unit focuses on the physical removal of pollutants, including an ultrasonic cleaning module and a microbubble and vortex water flow module. The ultrasonic cleaning module is equipped with a variable frequency drive circuit, supporting continuous stepless adjustment of output power (0-500W) and operating frequency (20-100kHz). Specifically, the low-frequency high-intensity mode (e.g., 20-40kHz, 300-500W) is suitable for tough root vegetables such as carrots and potatoes, utilizing the cavitation effect to generate microjets that powerfully remove surface wax layers and stubborn dirt; the high-frequency low-intensity mode (e.g., ... The 80-100kHz, 50-150W pump is suitable for delicate berries such as strawberries and blueberries, gently removing surface dirt without rupturing cells. The microbubble and vortex water flow module consists of a variable-speed pump, a microbubble generator, and a flow guide assembly. Adjusting the pump speed changes the vortex water flow intensity (using centrifugal force to remove surface impurities), and controlling the gas-liquid mixing ratio generates microbubbles of different sizes (the bursting of these bubbles generates localized high pressure and shear force, penetrating deep into crevices to remove dirt). This allows for flexible switching between gentle cleaning and powerful cleaning, suitable for fruits and vegetables with varying tolerance levels. The new technology unit focuses on green and efficient purification, employing a cold plasma jet array design. The plasma generator produces active oxygen and nitrogen species and ultraviolet light, achieving non-thermal sterilization and pesticide residue degradation without adding any chemical reagents. This unit is suitable for organic fruits and vegetables, high-value fresh-cut fruits and vegetables, and other scenarios with zero tolerance for chemical residues. It ensures purification effectiveness while maximizing the preservation of the original flavor and nutrients of fruits and vegetables, avoiding the quality damage caused by traditional high-temperature or chemical purification.

[0030] In one embodiment, the purification execution module is further configured to monitor the operating parameters of each technical purification unit in real time through an online sensor network, and feed back the monitored operating parameters to the intelligent decision module in real time; the intelligent decision module compares the fed-back real-time operating parameters with preset purification parameter thresholds, and fine-tunes the operating parameters of each technical purification unit according to the comparison results, forming a closed-loop control.

[0031] Specifically, a network of online sensors monitors key operating parameters of each purification unit in real time. For the chemical purification unit, pH, oxidation-reduction potential, and ozone concentration sensors are used to monitor core parameters such as the acidity / alkalinity of the electrolyzed water, hydroxyl radical activity, and ozone concentration. For the physical purification unit, flow, pressure, and turbidity sensors are used to monitor operating status such as water flow intensity, cleaning pressure, and cleaning solution turbidity. A temperature sensor is also included to ensure stable temperature during the purification process and prevent temperature fluctuations from affecting the quality of fruits and vegetables. The real-time operating parameters collected by the sensor network are synchronously fed back to the intelligent decision-making module via a data communication module. The intelligent decision-making module accurately compares the real-time operating parameters with preset purification parameter thresholds. If parameters deviate from the threshold range—for example, if the ozone concentration is lower than the preset threshold, resulting in insufficient sterilization, or if the water flow intensity is too high, potentially damaging fruits and vegetables—the module immediately generates a fine-tuning instruction, which is fed back to the purification execution module to adjust the corresponding operating parameters (such as increasing the ozone generator power or decreasing the water pump speed) until the parameters return to a reasonable range. This closed-loop control mechanism ensures that the purification process is always in an optimal state, avoiding insufficient purification or overtreatment due to environmental changes or batch differences in fruits and vegetables.

[0032] In one embodiment, the intelligent decision-making module has a built-in parameter deviation warning mechanism. When the real-time operating parameters fed back by the purification execution module exceed the purification parameter threshold for a preset duration, a local audible and visual warning is triggered.

[0033] Specifically, the intelligent decision-making module has a built-in parameter deviation early warning mechanism. Its core function is to respond to abnormal operating conditions in a timely manner. When the real-time operating parameters fed back by the purification execution module exceed the preset purification parameter threshold and the duration exceeds the preset time (such as 5 seconds), it is determined to be an abnormal operating condition, triggering a local audible and visual early warning. The buzzer emits a warning sound and the indicator light flashes to remind the operator to check the problem in time.

[0034] In one embodiment, the post-purification quality verification module includes a purification effect monitoring unit, a quality retention monitoring unit, and a sorting unit. The purification effect monitoring unit is used to detect the pesticide residue degradation rate, microbial kill rate, and heavy metal residue, and to verify whether the corresponding preset thresholds have been reached. The quality retention monitoring unit is used to retest the nutrient content, hardness, and surface color changes of fruits and vegetables, and to calculate the nutrient loss rate and hardness retention rate. The sorting unit is used to classify fruits and vegetables into qualified products, products awaiting re-inspection, and unqualified products based on the test results.

[0035] Specifically, the purification effect monitoring unit focuses on food safety indicators. It uses a rapid pesticide residue detector to quickly measure the degradation rate of common pesticide residues such as organophosphates and carbamates, verifying whether a preset threshold of ≥90% has been reached. A rapid microbial sensor captures characteristic fluorescence signals of pathogenic microorganisms, quantifying the microbial kill rate to ensure a safety standard of ≥99%. A heavy metal residue detection component screens for potential heavy metal contaminants, ensuring that residue levels meet national food safety standards and eliminating potential safety hazards at the source. The quality retention monitoring unit focuses on the integrity of fruit and vegetable quality. It uses a near-infrared spectroscopy probe to remeasure the content of soluble solids, vitamin C, and other nutrients, calculating the nutrient loss rate. A non-contact hardness detector remeasures the hardness of fruits and vegetables, assessing the hardness retention rate. A color sensor captures surface color changes, ensuring that the color deviation ΔE ≤ 2, preventing color deterioration caused by purification. The sorting unit is used to classify fruits and vegetables into qualified products, products awaiting re-inspection, and unqualified products based on the test results of the purification effect monitoring unit and the quality retention monitoring unit. Qualified products directly enter the subsequent packaging process, and traceability information is generated simultaneously. Products awaiting re-inspection are temporarily stored and re-enter the verification module for secondary testing to eliminate random errors. Unqualified products are then put into the re-inspection process. If the re-inspection still fails to meet the standards, they are directly diverted to the waste disposal channel to prevent unqualified products from entering the market.

[0036] In one embodiment, the fruit and vegetable product purification system based on quality assessment further includes a cloud-based digital optimization module, which comprises a data storage unit, a model optimization unit, and a traceability management unit. The data storage unit stores multi-dimensional quality parameters, purification control instructions, operating parameters of each technical purification unit, and test results for each batch of fruits and vegetables, forming a full-chain traceable database. The model optimization unit dynamically updates the expert rule base and reinforcement learning model parameters using reinforcement learning algorithms. The traceability management unit generates a unique traceability QR code for each batch of qualified products.

[0037] Specifically, the cloud-based digital optimization module includes a data storage unit, a model optimization unit, and a traceability management unit. The data storage unit constructs a complete, tamper-proof database, storing the entire data chain for each batch of fruits and vegetables, including multi-dimensional quality parameters, purification control instructions, operating parameters of each technical purification unit, and test results. All data is stored in batch-related associations, forming traceable data archives, providing a basis for subsequent problem investigation and process optimization. The model optimization unit, based on reinforcement learning algorithms, continuously mines effective information from the database. By comparing data from different batches of fruits and vegetables, it analyzes the adaptability and shortcomings of purification solutions, dynamically updating the expert rule base (such as adding exclusive processing rules for specific varieties of fruits and vegetables) and reinforcement learning model parameters (such as adjusting the weight coefficients of different quality indicators). This allows the system's decision-making accuracy to gradually improve with usage, becoming increasingly intelligent and quickly adapting to the characteristics of fruits and vegetables from new production areas and new varieties. The traceability management unit generates a unique traceability QR code for each batch of qualified products, which is linked to the entire data chain of that batch of fruits and vegetables.

[0038] In one embodiment, the fruit and vegetable product purification system based on quality assessment also includes a data communication module. The data communication module adopts a multi-mode communication architecture to realize real-time data transmission between modules.

[0039] Specifically, the data communication module, acting as a data transmission bridge between various modules of the system, adopts a multi-mode communication architecture to ensure the real-time performance, stability, and reliability of data transmission, providing support for the closed-loop operation of the system. The module integrates multiple communication methods such as Ethernet, Wi-Fi, and 5G, flexibly adapting to the communication needs of different modules. Specifically, for local short-range communication scenarios (such as the multi-dimensional quality perception module and data processing module, the intelligent decision-making module and the purification execution unit), Ethernet or Wi-Fi communication is used to achieve low-latency data interaction and ensure rapid transmission of real-time data. For remote communication scenarios (such as the intelligent decision-making module and the cloud-based digital optimization module), 5G communication technology is used, leveraging its high bandwidth, wide coverage, and low latency characteristics to achieve real-time uploading of data across the entire chain and rapid issuance of remote commands.

[0040] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A quality assessment based fruit and vegetable product sanitizing system, characterized by, It includes a multi-dimensional quality perception module, an intelligent decision-making module, a purification execution module, and a post-purification quality verification module; The multi-dimensional quality perception module is used to collect multi-dimensional quality parameters of fruits and vegetables in real time, generate quality feature vectors, and transmit the quality feature vectors to the intelligent decision-making module. The intelligent decision-making module is used to call a pre-set expert rule base based on the quality feature vector, combine it with a pre-trained reinforcement learning model, generate purification control instructions, and transmit the purification control instructions to the purification execution module. The purification control instructions include purification technology combination schemes, operating parameters of each purification technology unit, and cabin matching instructions. The purification execution module is used to drive each technical purification unit to start operation according to the purification control command after the fruits and vegetables enter the corresponding purification chamber according to the chamber matching command. The purification quality verification module is used to detect the pollutant removal effect and the fruit and vegetable quality retention rate after the fruits and vegetables have been purified, and to classify the fruits and vegetables into qualified products, products to be re-inspected, and unqualified products based on the test results. The multi-dimensional quality perception module includes a visual perception unit, a texture characteristic perception unit, and a safety risk perception unit. The visual perception unit is used to acquire the shape and color features of fruits and vegetables through a high-resolution color camera and multispectral / hyperspectral imaging components, identify internal defects and component distribution of fruits and vegetables, and non-destructively detect the soluble solids content, total acidity and sugar-acid ratio of fruits and vegetables through a partial least squares regression model. The texture characteristic sensing unit is used to evaluate the hardness and elastic texture parameters of fruits and vegetables online using a non-contact acoustic vibration sensor or an optical coherence tomography detector. The safety risk perception unit is used to monitor volatile organic compounds in fruits and vegetables, provide early warning of microbial contamination risk levels, and quickly screen for elemental pollutants.

2. A quality evaluation based fruit and vegetable product cleaning system as claimed in claim 1, wherein, It also includes a data processing module, which is communicatively connected to the multi-dimensional quality perception module; The data processing module is used to acquire the multi-dimensional quality parameters of fruits and vegetables collected by the multi-dimensional quality perception module, perform filtering, noise reduction and normalization processing on the multi-dimensional quality parameters of fruits and vegetables, remove outliers, and feed back the processed multi-dimensional quality parameters of fruits and vegetables to the multi-dimensional quality perception module.

3. A quality evaluation based fruit and vegetable product cleaning system as claimed in claim 1, wherein, It also includes an external quality screening module, which is located at the front end of the multi-dimensional quality perception module; The external quality screening module is used to collect images of the appearance of fruits and vegetables, analyze the morphological integrity and surface condition of fruits and vegetables through image recognition algorithms, identify unqualified fruits and vegetables that are severely rotten, deformed, or have surface damage areas exceeding a preset threshold, and trigger the sorting execution mechanism to automatically remove the unqualified fruits and vegetables from the processing flow.

4. The fruit and vegetable product purification system based on quality assessment according to claim 1, characterized in that, The technical purification unit includes a chemical purification unit, a physical purification unit, and a novel technology unit. Each technical purification unit operates independently or collaboratively according to the purification technology combination scheme. The chemical purification unit includes a hydroxyl water ion generating module and an ozone water treatment module. The hydroxyl water ion generating module is equipped with an adjustable electrolysis power supply. By adjusting the electrolysis current, the generation rate of hydroxyl free radicals is controlled to specifically degrade pollutants on the surface and shallow layers of fruits and vegetables. The ozone water treatment module is used to efficiently kill pathogenic microorganisms on the surface of fruits and vegetables by controlling the ozone concentration and reaction time. The physical purification unit includes an ultrasonic cleaning module and a microbubble and vortex water flow module. The ultrasonic cleaning module is equipped with a variable frequency drive circuit. By adjusting the output power and working frequency, it performs differentiated physical peeling and cleaning for fruits and vegetables with different textures. The microbubble and vortex water flow module consists of a variable pump, a microbubble generator, and a flow guiding component. By adjusting the pump speed, the intensity of the vortex water flow is changed, and the gas-liquid mixing ratio is controlled to generate microbubbles of different particle sizes, realizing flexible switching between gentle cleaning and powerful decontamination to adapt to fruits and vegetables with different tolerance levels. The novel technology unit is used to generate reactive oxygen and nitrogen species and ultraviolet light through a plasma generator, so as to achieve non-thermal sterilization and pesticide residue degradation without the need to add chemical reagents.

5. The fruit and vegetable product purification system based on quality assessment according to claim 1, characterized in that, The purification execution module is also used to monitor the operating parameters of each technical purification unit in real time through an online sensor network, and to feed back the monitored operating parameters to the intelligent decision-making module in real time. The intelligent decision-making module compares the real-time operating parameters fed back with the preset purification parameter thresholds, and fine-tunes the operating parameters of each technical purification unit based on the comparison results, forming a closed-loop control.

6. The fruit and vegetable product purification system based on quality assessment according to claim 5, characterized in that, The intelligent decision-making module has a built-in parameter deviation warning mechanism. When the real-time operating parameters fed back by the purification execution module exceed the purification parameter threshold for a preset duration, a local audible and visual warning is triggered.

7. The fruit and vegetable product purification system based on quality assessment according to claim 1, characterized in that, The post-purification quality verification module includes a purification effect monitoring unit, a quality retention monitoring unit, and a sorting unit. The purification effect monitoring unit is used to detect the pesticide residue degradation rate, microbial kill rate and heavy metal residue, and to verify whether the corresponding preset threshold has been reached. The quality retention monitoring unit is used to retest the nutrient content, hardness, and surface color changes of fruits and vegetables, and to calculate the nutrient loss rate and hardness retention rate. The sorting unit is used to classify fruits and vegetables into qualified products, products awaiting re-inspection, and unqualified products based on the test results.

8. The fruit and vegetable product purification system based on quality assessment according to claim 1, characterized in that, It also includes a cloud-based digital optimization module, which comprises a data storage unit, a model optimization unit, and a traceability management unit; The data storage unit is used to store multi-dimensional quality parameters, purification control instructions, operating parameters of each technical purification unit, and test results for each batch of fruits and vegetables, forming a traceable database for the entire chain. The model optimization unit is used to dynamically update the expert rule base and reinforcement learning model parameters through reinforcement learning algorithms; The traceability management unit is used to generate a unique traceability QR code for each batch of qualified products.

9. The fruit and vegetable product purification system based on quality assessment according to claim 1, characterized in that, It also includes a data communication module, which adopts a multi-mode communication architecture to realize real-time data transmission between modules.

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