Agricultural product quality sampling detection system

Abstract

The invention discloses an agricultural product quality sampling detection system, which uses a non-contact measurement technology, combines a high-resolution camera and an infrared sensor, detects agricultural products packaged by indirect cold plasma and modified atmosphere, automatically captures tiny changes of the products and analyzes problems. By utilizing visual inspection equipment, the system can automatically identify and mark suspected defective products and then transfer the suspected defective products to a to-be-detected area for analysis; the system also comprises a flexible pressure test and a gas sensor detection, so as to evaluate the physical pressure resistance of the agricultural product and the change of gas components in the package, and ensure the freshness and safety of the product. Through pH value and microbiological detection, the system can ensure the hygienic standard of agricultural products; through integration of the data cloud platform and the digital twin model, centralized management and intelligent analysis of detection data are realized, and visual decision support is provided for operators; according to the invention, the labor intensity and error rate of manual detection are reduced, and the efficiency and accuracy of the detection process are improved.

Description

Technical Field

[0001] The invention relates to the technical field of agricultural product quality sampling inspection, and in particular to an agricultural product quality sampling inspection system. Background Art

[0002] Agricultural product quality inspection technology continues to develop with scientific and technological progress, but traditional methods mainly rely on manual operations, which are inefficient and highly subjective. The application of non-contact measurement technologies such as photoelectric and electromagnetic technologies has improved the speed and accuracy of inspection, but still needs further integration to achieve full automation. In addition, although modified atmosphere packaging technology has effectively extended the shelf life of agricultural products, there is still room for improvement in packaging quality inspection.

[0003] Modified atmosphere packaging technology can effectively extend the shelf life of food by precisely controlling the ratio of oxygen, carbon dioxide and nitrogen in the package29; combined with indirect cold plasma technology, it can use the generated active substances to perform non-thermal sterilization on the food surface without direct contact with the food, further inhibiting the growth of microorganisms and maintaining the freshness of the food.

[0004] Modern agricultural product quality inspection systems have begun to integrate intelligent analysis systems, using computer image analysis technology to achieve target identification and tracking, thereby improving the level of automation in inspections. Digital twin technology, as an emerging solution, creates virtual models of agricultural products and uses real-time data for simulation and monitoring, providing new possibilities for optimizing inspection processes and improving efficiency. The application of these technologies helps reduce human errors and improve the consistency and reliability of inspections.

[0005] The application of data cloud platform and big data technology in agricultural product quality testing enables the testing system to collect and analyze large amounts of data, providing deeper insights and predictions; through data modeling and analysis, the testing system can not only monitor the quality of agricultural products in real time, but also predict potential problems and take measures in advance; in addition, the accuracy of microbial testing technology is crucial to ensuring food safety. Modern testing technology can accurately analyze the microbial content of samples to ensure that agricultural products meet safety standards.

[0006] Therefore, it is necessary to provide a kind of agricultural product quality sampling and testing system to solve the above-mentioned technical problems. Summary of the invention

[0007] The invention overcomes the shortcomings of the prior art and provides a sampling detection system for agricultural product quality.

[0008] To achieve the above object, the technical solution adopted by the present invention is: a system for sampling and detecting quality of agricultural products, comprising the following steps:

[0009] S1: Place the agricultural products packaged with indirect cold plasma combined with modified atmosphere at the starting position of the production line to ensure that each agricultural product is placed separately to facilitate the subsequent testing process;

[0010] S2: Use high-resolution cameras and infrared sensors to perform non-contact measurements of agricultural products, ensuring that even the slightest changes in packaging can be captured;

[0011] S3: Use visual inspection equipment to analyze product images, identify potential problem products according to preset standards, automatically mark the suspected problem products, and transfer them from the main pipeline to the area to be inspected;

[0012] S4: Perform a flexible pressure test, set the pressure range of the flexible pressure device to apply a pressure of 0.5-1.5 kgf, and set the duration of the pressure test to last for 5 seconds;

[0013] S5: Perform gas sensor detection to enable the gas sensor to detect whether the concentration changes of oxygen, carbon dioxide and ethylene are abnormal;

[0014] S6: If the flexible pressure test is passed, take samples of the suspected problematic products, set the sample size to 10g, conduct pH index test and microbial test, and adjust the ratio of oxygen and carbon dioxide in the modified atmosphere packaging according to the test results;

[0015] S7: The data cloud platform collects all test data, matches it with the digital twin model, automatically calculates the index value, and displays it in a three-dimensional image on the control terminal. The operator of the control terminal adjusts the equipment parameters according to the displayed data to optimize the production process.

[0016] S8: Through iterative optimization, 45% of the collected data in the next process cycle is used as verification data to test the working efficiency and product quality of the automated production line; the system automatically records the results of each test and adjustment to provide data support and optimization suggestions for future production.

[0017] In a preferred embodiment of the present invention, in S1, the interval between each piece of agricultural product is set to 5-10 cm.

[0018] In a preferred embodiment of the present invention, in said S2, the scanning resolution of the high-resolution camera is set to 300 dpi, and the temperature detection threshold of the infrared sensor is set in the range of -10-+10°C.

[0019] In a preferred embodiment of the present invention, in S3, the preset standard is: the area of ​​the damaged package is greater than 5cm 2 Or products with surface defects, irregular shapes, or inconsistent maturity.

[0020] In a preferred embodiment of the present invention, in S5, a threshold value of gas concentration is set, and a decrease in oxygen concentration exceeding 5% or an increase in ethylene concentration exceeding 1 ppm is regarded as abnormal.

[0021] In a preferred embodiment of the present invention, in S5, the detection frequency of the gas sensor is set to 0.2 Hz to monitor the change of gas concentration in real time.

[0022] In a preferred embodiment of the present invention, in said S5, the gas sensors are arranged on the top and sides of the package to comprehensively monitor the changes in gas composition.

[0023] In a preferred embodiment of the present invention, in S6, when detecting the pH value index, the accuracy of the pH value is set to 0.01, and the number of repetitions of the pH value index detection is set to 3 times.

[0024] In a preferred embodiment of the present invention, in S6, when performing microbial detection, the threshold value of the total number of colonies is set to a total number of colonies per gram of sample not exceeding 10 4 CFU, and the culture time range is set to 24-48h.

[0025] In a preferred embodiment of the present invention, a system for sampling and detecting agricultural product quality includes: an automatic conveyor belt, a high-resolution camera, an infrared sensor, a visual inspection device, a flexible pressure testing device, a gas sensor, a pH value and microbial detection equipment, a data cloud platform and a digital twin model.

[0026] The present invention solves the defects existing in the background technology and has the following beneficial effects:

[0027] (1) The present invention provides a sampling and testing system for agricultural product quality, which greatly improves the testing efficiency and accuracy through non-contact measurement and automated testing process. It uses high-resolution cameras and infrared sensors to capture minute changes in agricultural products, and combines visual inspection equipment to analyze product images, which can effectively identify potential problem products. In addition, by setting preset standards, the system can automatically mark suspected problem products and transfer them to the area to be tested, reducing the labor intensity and human errors of manual testing, and ensuring the consistency and reliability of agricultural product quality.

[0028] (2) The present invention provides a sampling and detection system for agricultural product quality. By adopting a method combining flexible pressure testing and gas sensor detection, the physical and chemical properties of agricultural products can be comprehensively evaluated. By setting a precise pressure range and duration, the system can perform detailed pressure testing on agricultural products to ensure the packaging integrity and pressure resistance of agricultural products. At the same time, the gas sensor can monitor the concentration changes of oxygen, carbon dioxide and ethylene in real time, detect abnormal conditions in a timely manner, and provide a scientific basis for the preservation and storage of agricultural products. This comprehensive detection method helps to improve the overall quality and market competitiveness of agricultural products.

[0029] (3) The present invention provides a sampling and testing system for agricultural product quality, which is equipped with a data cloud platform and a digital twin model to realize centralized management and intelligent analysis of test data. By collecting all test data and matching them with the digital twin model, the system can automatically calculate the index values ​​and display them in three-dimensional images, providing intuitive decision support for operators. In addition, the system continuously adjusts equipment parameters and production processes through iterative optimization and uses collected data as verification to achieve continuous improvement in production efficiency and product quality. The system automatically records test and adjustment results to provide valuable data support and optimization suggestions for future production, which helps enterprises realize intelligent and refined management. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work.

[0031] Figure 1 It is a flow chart of a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0034] like Figure 1As shown, the present invention provides a system for sampling and detecting quality of agricultural products, comprising the following steps:

[0035] S1: Place the indirect cold plasma combined with modified atmosphere packaged agricultural products such as cherry tomatoes, cucumbers and lettuce at the starting position of the production line, ensuring that each agricultural product is placed separately, and the interval between each agricultural product is set to 5-10cm to facilitate the subsequent testing process;

[0036] S2: Use high-resolution cameras and infrared sensors to perform non-contact measurement of agricultural products. The scanning resolution of the high-resolution camera is set to 300dpi, and the temperature detection threshold of the infrared sensor is set in the range of -10-+10℃ to ensure that slight changes in the packaging can be captured;

[0037] S3: Use visual inspection equipment to analyze product images, identify potential problem products according to preset standards, automatically mark the suspected problem products, and transfer them from the mainstream pipeline to the inspection area. The preset standard is: the area of ​​package damage is greater than 5cm 2 or products with surface defects, irregular shapes, or inconsistent maturity;

[0038] S4: Perform a flexible pressure test, set the pressure range of the flexible pressure device to apply a pressure of 0.5-1.5 kgf, and set the duration of the pressure test to last for 5 seconds;

[0039] S5: Perform gas sensor detection to enable the gas sensor to detect whether the concentration changes of oxygen, carbon dioxide and ethylene are abnormal. When the oxygen concentration drops by more than 5% or the ethylene concentration rises by more than 1ppm, it is considered abnormal. The detection frequency of the gas sensor is set to 0.2Hz to monitor the changes in gas concentration in real time. The gas sensors are set on the top and side of the package to comprehensively monitor the changes in gas composition;

[0040] S6: If the flexible pressure test is passed, the suspected problematic product is sampled, the sample size is set to 10g, and pH index detection and microbial detection are performed. When the pH index is detected, the pH accuracy is set to 0.01, the number of repetitions of the pH index detection is set to 3 times, and when the microbial detection is performed, the threshold value of the total number of colonies is set to no more than 10 colonies per gram of sample. 4 CFU, and set the culture time range to 24-48h. According to the test results, adjust the ratio of oxygen and carbon dioxide in the modified atmosphere packaging to 8-12% and 1.5-2.5% respectively.

[0041] S7: The data cloud platform collects all test data, matches it with the digital twin model, automatically calculates the index value, and displays it in a three-dimensional image on the control terminal. The operator of the control terminal adjusts the equipment parameters according to the displayed data to optimize the production process.

[0042] S8: Through iterative optimization, 45% of the collected data in the next process cycle is used as verification data to test the working efficiency and product quality of the automated production line; the system automatically records the results of each test and adjustment to provide data support and optimization suggestions for future production.

[0043] It should be noted that:

[0044] S1: Ensure the efficiency and accuracy of the inspection process by placing each agricultural product separately and keeping a distance of 5-10cm. This method not only avoids interference between products, but also maintains the smooth operation of the production line, thus ensuring the continuity and consistency of inspection.

[0045] S2: Non-contact measurement using a 300dpi high-resolution camera and infrared sensor provides a non-destructive way to inspect agricultural products and effectively protect the integrity of the products. This measurement can capture small changes in product packaging and temperature, providing important data support for early detection of potential problems.

[0046] S3: Automated visual inspection equipment significantly improves the efficiency of identifying potentially problematic products. Through preset standards, the equipment can quickly and automatically identify damaged or deformed products, reducing the need for manual inspection and possible errors, and improving the accuracy of the entire inspection process.

[0047] S4: Flexible pressure test evaluates the pressure resistance of product packaging by simulating actual transportation conditions. Applying 0.5-1.5kgf of pressure for 5 seconds helps to screen out products with fragile structures, ensuring that only products that meet the pressure resistance requirements can enter the market and improve the market access standards of products.

[0048] S5: Gas sensor detection provides an effective means to promptly detect product freshness and deterioration by monitoring the concentration changes of oxygen, carbon dioxide and ethylene in real time. The detection frequency of 0.2Hz ensures a rapid response to changes in gas composition, providing early indicators for evaluating product quality and safety.

[0049] S6: In-depth pH and microbiological testing of suspected problematic products ensures food safety. Accurate pH testing and microbial counts help assess the hygienic condition of the product. Based on these test results, the ratio of oxygen and carbon dioxide in the modified atmosphere packaging is adjusted to optimize the preservation effect and extend the shelf life of the product.

[0050] S7: Use the data cloud platform and digital twin model to realize real-time collection and analysis of agricultural product testing data. This step enables operators to quickly understand the current production status through the intuitive display of three-dimensional images on the control terminal, and make timely equipment parameter adjustments based on data analysis results. This data-based decision-making process not only improves production efficiency, but also ensures consistency and optimization of product quality.

[0051] S8: Through iterative optimization and automatic system recording, we can continuously monitor and improve the efficiency and product quality of the automated production line. We use 45% of the collected data in the next process cycle as verification to ensure the stability and reliability of the production process. At the same time, each test and adjustment result recorded by the system provides valuable data support and optimization suggestions for future production, which helps to accumulate production experience, form a knowledge base, and lay the foundation for long-term development.

[0052] A sampling and testing system for agricultural product quality, comprising: an automatic conveyor belt, a high-resolution camera, an infrared sensor, a visual inspection device, a flexible pressure testing device, a gas sensor, a pH value and microbial detection equipment, a data cloud platform and a digital twin model.

[0053] It should be noted that: automatic conveyor belts are used to transport agricultural products to the inspection area; high-resolution cameras are used to capture images of agricultural products; infrared sensors are used to detect the surface temperature of agricultural products; visual inspection equipment is used to analyze images and identify problematic products; flexible pressure testing devices are used to simulate extrusion during transportation; gas sensors are used to detect gas concentration in the package.

[0054] Embodiment 1:

[0055] Indirect cold plasma combined with modified atmosphere packaging method:

[0056] Choose fresh agricultural products: Choose cucumbers that are 90% mature, brightly colored, uniform in size, and free of mechanical damage and pests and diseases.

[0057] Cleaning and pretreatment: Wash the cucumbers with clean water, soak them for about 10 minutes, take them out and absorb the surface moisture.

[0058] Modified atmosphere packaging: Place the cucumbers in a special modified atmosphere packaging bag and fill it with 10% oxygen, 2% carbon dioxide and 88% nitrogen.

[0059] Cold plasma treatment: The packaged cucumbers are transported to a high-voltage electric field through a production line. The medium surrounding the food is used to generate photoelectrons, ions and free radicals, which come into contact with the surface of microorganisms, causing their cells to be destroyed, thereby achieving a sterilization effect.

[0060] System composition:

[0061] Automatic conveyor belt for transporting cucumbers to the inspection area;

[0062] a high-resolution camera to capture images of cucumbers;

[0063] Infrared sensor, used to detect the surface temperature of cucumber;

[0064] Visual inspection equipment to analyze images and identify problematic products;

[0065] Flexible pressure test device, used to simulate the squeezing during transportation;

[0066] Gas sensor, used to detect gas concentration inside the package;

[0067] pH and microbiological testing equipment to assess the freshness and safety of cucumbers;

[0068] Data cloud platform and digital twin models for data collection, analysis and equipment monitoring;

[0069] Implementation steps:

[0070] S1: Place the cucumbers at the starting position of the automatic conveyor, ensuring that there is an 8cm gap between each product.

[0071] S2: Use a high-resolution camera to scan the cucumbers, set the resolution to 300dpi to ensure image clarity; the infrared sensor detection temperature range is set to -5-+5℃.

[0072] S3: The visual inspection equipment analyzes the image and automatically identifies the following issues:

[0073] Package damage: Identify the package damage area larger than 5cm 2 products.

[0074] Product deformation: Identify products with surface defects, irregular shapes, and inconsistent maturity of cucumbers.

[0075] S4: Perform a flexible pressure test on the suspected problematic product, applying a pressure of 1.0kgf for 5 seconds.

[0076] S5: The gas sensor detects the concentration of oxygen, carbon dioxide and ethylene in the package at a frequency of 0.2Hz. When the oxygen concentration drops by more than 5% or the ethylene concentration rises by more than 1ppm, the system will sound an alarm and the suspected problematic products will be automatically marked and transferred to the inspection area.

[0077] S6: Take 10g of sample from the product that has passed the flexible pressure test, set the pH value detection accuracy to 0.01, and repeat the test three times. The threshold for the total number of colonies in the microbial test is set to no more than 10 per gram of sample. 3 CFU.

[0078] S7: The data cloud platform collects all inspection data, matches it with the digital twin model, automatically calculates the indicator values, and displays them in the form of three-dimensional images on the control terminal; the control terminal operator adjusts the equipment parameters according to the displayed data and optimizes the production process.

[0079] S8: Through iterative optimization, 45% of the collected data in the next process cycle is used as verification data to test the working efficiency and product quality of the automated production line; the system automatically records the results of each test and adjustment to provide data support and optimization suggestions for future production.

[0080] In summary:

[0081] The quality and safety of agricultural products are ensured through a series of inspection steps. The system design includes automatic conveyor belts, high-resolution cameras, infrared sensors, visual inspection equipment, flexible pressure testing devices, gas sensors, pH and microbial detection equipment, as well as data cloud platforms and digital twin models. These components work together to achieve full process coverage from individual placement of agricultural products, non-contact measurement, image analysis, pressure testing, to gas concentration monitoring and in-depth chemical and microbial testing. The system can collect data in real time, analyze it using a digital twin model, and display it intuitively in the form of three-dimensional images, so that operators can adjust equipment parameters in a timely manner and optimize production processes.

[0082] Automation reduces manual intervention and improves the efficiency and accuracy of detection. Secondly, the real-time data collection and analysis capabilities enable the system to respond quickly to any quality changes, providing strong protection for the freshness and safety of agricultural products. In addition, the iterative optimization function of the system allows it to continuously learn and self-improve based on the collected data, thereby improving production efficiency and product quality. The detection and adjustment results automatically recorded by the system not only provide data support for current production, but also lay the foundation for future production optimization and knowledge accumulation.

[0083] The above is based on the ideal embodiment of the present invention. Through the above description, relevant personnel can make various changes and modifications without departing from the technical concept of the present invention. The technical scope of the present invention is not limited to the content in the specification, and the technical scope must be determined according to the scope of the claims.

Claims

1. A method for sampling and detecting the quality of agricultural products, characterized in that: The following steps are involved: S1: Place the agricultural products packaged with indirect cold plasma combined with modified atmosphere at the starting position of the production line to ensure that each agricultural product is placed separately to facilitate the subsequent testing process; S2: Use high-resolution cameras and infrared sensors to perform non-contact measurements of agricultural products, ensuring that even the slightest changes in packaging can be captured; S3: Use visual inspection equipment to analyze product images, identify potential problem products according to preset standards, automatically mark the suspected problem products, and transfer them from the main pipeline to the area to be inspected; S4: Perform a flexible pressure test, set the pressure range of the flexible pressure device to apply a pressure of 0.5-1.5 kgf, and set the duration of the pressure test to last for 5 seconds; S5: Perform gas sensor detection to enable the gas sensor to detect whether the concentration changes of oxygen, carbon dioxide and ethylene are abnormal; S6: If the flexible pressure test is passed, take samples of the suspected problematic products, set the sample size to 10g, conduct pH index test and microbial test, and adjust the ratio of oxygen and carbon dioxide in the modified atmosphere packaging according to the test results; S7: The data cloud platform collects all test data, matches it with the digital twin model, automatically calculates the index value, and displays it in a three-dimensional image on the control terminal. The operator of the control terminal adjusts the equipment parameters according to the displayed data to optimize the production process. S8: Through iterative optimization, 45% of the collected data in the next process cycle is used as verification data to test the working efficiency and product quality of the automated production line; the system automatically records the results of each test and adjustment to provide data support and optimization suggestions for future production.

2. A method for sampling and detecting agricultural product quality according to claim 1, characterized in that: In S1, the interval between each piece of agricultural product is set to 5-10 cm.

3. A method for sampling and detecting agricultural product quality according to claim 1, characterized in that: In S2, the scanning resolution of the high-resolution camera is set to 300 dpi, and the temperature detection threshold of the infrared sensor is set in the range of -10-+10°C.

4. A method for sampling and detecting agricultural product quality according to claim 1, characterized in that: In S3, the preset standard is: the area of ​​the damaged package is greater than 5cm 2 Or products with surface defects, irregular shapes, or inconsistent maturity.

5. The method for sampling and detecting agricultural product quality according to claim 1, characterized in that: In S5, a threshold value of gas concentration is set, and a decrease in oxygen concentration exceeding 5% or an increase in ethylene concentration exceeding 1 ppm is regarded as abnormal.

6. A method for sampling and detecting agricultural product quality according to claim 1, characterized in that: In S5, the detection frequency of the gas sensor is set to 0.2 Hz to monitor the change of gas concentration in real time.

7. A method for sampling and detecting agricultural product quality according to claim 1, characterized in that: In the S5, the gas sensors are located on the top and sides of the package to comprehensively monitor changes in gas composition.

8. A method for sampling and testing agricultural product quality according to claim 1, characterized in that: In the step S6, when detecting the pH value index, the accuracy of the pH value is set to 0.01, and the number of repetitions of the pH value index detection is set to 3 times.

9. A method for sampling and testing agricultural product quality according to claim 1, characterized in that: In S6, when performing microbial detection, the threshold of the total number of colonies is set to a total number of colonies per gram of sample not exceeding 10 4 CFU, and the culture time range is set to 24-48h.

10. A sampling and testing system for agricultural product quality according to any one of claims 1 to 9, characterized in that: include: Automatic conveyor belts, high-resolution cameras, infrared sensors, visual inspection equipment, flexible pressure testing devices, gas sensors, pH and microbial testing equipment, data cloud platforms and digital twin models.

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