A method for verifying the authenticity of agricultural product traceability

Abstract

The present invention provides a method for verifying the authenticity of agricultural product traceability, including: a "three-party verification" traceability verification system composed of traceability information from an enterprise end, a management end, and a monitoring end; when obtaining the traceability verification needs of consumers, the traceability information from the enterprise end is returned to the consumer; if the consumer has doubts about the traceability information from the enterprise end, the traceability information from the management end is returned to the consumer, and the comparison of the traceability information from the enterprise end and the management end is presented to the consumer; if the consumer still has doubts about the traceability information from the enterprise end, the traceability information from the monitoring end is returned to the consumer, and the comparison of the enterprise end, the management end, and the monitoring end is presented to the consumer. The present invention introduces "three-party verification" to judge the authenticity of the traceability information, fills the gap in the traceability verification industry, effectively avoids the verification defects caused by the falsification of source traceability information, comprehensively offsets consumer doubts, and improves the social recognition of the agricultural product traceability industry.

Description

Technical Field

[0001] The present invention belongs to the technical field of agricultural product traceability, and in particular relates to a method for verifying the authenticity of agricultural product traceability. Background Art

[0002] At present, the application of agricultural product traceability has become relatively common, but the traceability information is mainly uploaded by producers. Producers may intentionally upload false information when uploading information to avoid consumers from buying the product after learning the real information and to prevent the leakage of the company's sensitive information, such as inventory information, production information, etc. Therefore, the authenticity and accuracy of traceability are questionable, resulting in low consumer recognition of traceability products, affecting the further development of the agricultural product traceability industry. Summary of the invention

[0003] In view of the above-mentioned deficiencies in the prior art, the present invention provides a method for verifying the authenticity of agricultural product traceability to solve the above-mentioned technical problems.

[0004] In a first aspect, the present invention provides a method for verifying the authenticity of agricultural product traceability, comprising:

[0005] The "three-party verification" traceability verification system consists of traceability information from the enterprise side, management side, and monitoring side. Among them, the traceability information on the enterprise side includes: agricultural records and operation records directly entered and maintained by production enterprises; the traceability information on the management side includes real-time data directly uploaded by data collection devices in all traceability links and maintained by IoT suppliers; the traceability information on the monitoring side includes real production videos of enterprises recorded by high-definition camera equipment at each traceability link of agricultural products;

[0006] When obtaining the traceability verification requirements of consumers, the traceability information on the enterprise side is returned to the consumers;

[0007] If the consumer has doubts about the traceability information on the enterprise side, the traceability information on the management side will be returned to the consumer, and the comparison of the traceability information on the enterprise side and the management side will be presented to the consumer;

[0008] If the consumer still has doubts about the traceability information on the enterprise side, the traceability information on the monitoring side will be returned to the consumer, and the comparison between the enterprise side, management side, and monitoring side will be presented to the consumer;

[0009] If consumers still have doubts about the authenticity of the traceability information, they can report it.

[0010] Furthermore, it also includes: when returning the traceability information to the consumer, presenting a comparison of the traceability information of all parties, and reminding the consumer of the permissible threshold value for each parameter during the comparison.

[0011] Furthermore, it also includes: when the comparison of the traceability information on the enterprise side and the management side is presented to consumers, each traceability link on the management side can select one of the data collection devices for comparison.

[0012] Furthermore, it also includes: if the final consumer still has doubts about the traceability information, he or she can warn the enterprise or management side to make corrections on their own.

[0013] Furthermore, automatic verification can be achieved, including:

[0014] In response to the need for authenticity verification of a certain agricultural product, the traceability code of the agricultural product is obtained;

[0015] According to the traceability code of the agricultural product, inquiries are made at the enterprise end, the management end, and the monitoring end to obtain the traceability information of the agricultural product, the target parameters included in the traceability information, and the monitoring image;

[0016] Match the target parameters of the enterprise side and the management side;

[0017] Perform numerical comparison between successfully matched target parameters. Before numerical comparison, unify the unit and data type to determine whether the target parameter is a fixed value parameter or a tolerable parameter.

[0018] If it is a fixed value parameter, it is considered qualified only when the numerical comparison is completely consistent; if it is a tolerable parameter, it is considered qualified when the numerical difference does not exceed a preset percentage of one of the numerical values;

[0019] The target parameters that have not been successfully matched and whose value comparison fails are integrated into abnormal parameters;

[0020] The abnormal parameters and monitoring images are delivered to manual verification as automatic verification results.

[0021] Furthermore, matching the target parameters of the enterprise end and the management end with respect to their correlation includes:

[0022] The field name of the target parameter is extracted, and a semantic matching model is created to determine whether the target parameters of the enterprise end and the management end match; the semantic matching model is a deep semantic matching model (Convolutional Latent Semantic Model, referred to as CLSM), and the training sample includes two parameter field names in the traceability information as input, and the semantic similarity or dissimilarity of the two parameter field names is manually annotated as output, and the semantic matching model is iteratively trained as new agricultural product varieties are added.

[0023] Further, the determining whether the target parameter is a fixed value parameter or a tolerable parameter includes:

[0024] Construct an SVM classifier and train it using commonly used fixed value parameters and tolerance parameters;

[0025] The SVM classifier input vector is the field name of the target parameter, and the output vector is the classification result of the fixed value parameter or the tolerable parameter.

[0026] The beneficial effects of the present invention are as follows: the present invention introduces "three-party verification" to determine the authenticity of traceability information, fills the gap in the traceability verification industry, effectively avoids verification defects caused by falsification of source traceability information, comprehensively offsets consumer concerns, and improves the social recognition of the agricultural product traceability industry.

[0027] In addition, the invention has a reliable design principle, a simple structure and a very broad application prospect. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] 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 will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0029] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings 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 should fall within the scope of protection of the present invention.

[0031] The most common and technologically advanced traceability information verification solution on the market is the traceability verification solution based on blockchain technology. This technical solution mainly uses the characteristics of blockchain that cannot be tampered with and decentralized for verification. This solution mainly determines the authenticity of data and is applicable to multiple industries, but if the traceability information provided by the original enterprise end is false, it cannot be detected.

[0032] Therefore, the verification method provided by the present invention fills the gap in the traceability verification industry by introducing the "three-party verification" system, verifies the traceability information of agricultural products through self-verification, third-party verification, and consumer verification, and can make judgments from the source, fill the gap in the industry, and is applicable to agricultural products (mainly plant-based agricultural products). Relatively speaking, it has lower costs, stronger pertinence, and better applicability.

[0033] The embodiment of the present invention provides a method for verifying the authenticity of agricultural product traceability, including: a "three-party verification" traceability verification system consisting of traceability information from an enterprise end, a management end, and a monitoring end;

[0034] Among them, the traceability information on the enterprise side includes: agricultural records and operation records directly entered and maintained by production enterprises; the traceability information on the management side includes real-time data directly uploaded by data collection devices in all traceability links and maintained by IoT suppliers; the traceability information on the monitoring side includes the real production videos of enterprises recorded by high-definition camera equipment in each traceability link of agricultural products;

[0035] S1. When obtaining the traceability verification requirements of consumers, the traceability information on the enterprise side is returned to the consumers;

[0036] S2. If the consumer has doubts about the traceability information on the enterprise side, the traceability information on the management side will be returned to the consumer, and the comparison of the traceability information on the enterprise side and the management side will be presented to the consumer;

[0037] S3. If the consumer still has doubts about the traceability information on the enterprise side, the traceability information on the monitoring side will be returned to the consumer, and the comparison between the enterprise side, management side, and monitoring side will be presented to the consumer;

[0038] S4. If consumers still have doubts about the authenticity of the traceability information, they can report it.

[0039] In the "three-party verification" traceability verification system provided in this embodiment, the traceability information consists of three parts: the first part is the traceability information on the enterprise side, which comes directly from the production enterprise, and is information manually recorded by farmers and operators through mobile phone APP, including agricultural records and operation records. The enterprise is responsible for data maintenance and authenticity assurance of this part of the data. The second part is the traceability information on the management side, which comes directly from the real-time data obtained by the IoT devices, including soil detectors (providing values ​​of parameters such as pH, heavy metal content, and nutrient content), field meteorological stations (providing values ​​of parameters such as temperature, humidity, rainfall, wind speed, air quality index, PM2.5, etc.), smart door systems (providing values ​​of parameters such as in-and-out information), temperature and humidity management systems (providing values ​​of parameters such as temperature and humidity during transportation), GPS devices (providing values ​​of positioning parameters), rapid inspection equipment (providing rapid inspection records and rapid inspection results), etc., which are directly uploaded to the website through IoT devices. This part of the data is provided by the IoT equipment supplier, who is responsible for data maintenance and authenticity assurance; the third part is the traceability information on the monitoring side, which records the actual production situation of the enterprise through high-definition cameras installed in key locations such as planting bases, processing workshops, and warehouses. This part of the data is provided by the traceability platform, which is responsible for data maintenance.

[0040] The present invention integrates the traceability information of the entire agricultural product industry chain based on the above verification method, and introduces advanced information technology integrated application to obtain traceability information according to different links, avoid information omissions, and ensure the data volume of the subsequent verification process, which specifically includes the following three links:

[0041] 1. Determine the key points of the traceability process. Taking fresh fruit as an example, the key points of traceability mainly include the following contents.

[0042] Breeding information:

[0043] Seed (seedling) identification information: seed (seedling) name, batch number, quantity, and specifications;

[0044] Parent information: seed (seedling) "parent" variety, batch number, quantity, specification;

[0045] Breeding information: breeding time, variety, quantity.

[0046] Planting information:

[0047] Information on batching and sub-batch: seedling name, original batch number, origin, quantity and specification, and newly generated batch number;

[0048] Product identification: name, batch number, quantity and specifications;

[0049] Base information: base environment, soil information, temperature information, water source information, etc.;

[0050] Water and fertilizer management information: fertilizer type, time, quantity, and operator; irrigation time, method, and operator;

[0051] Pest control information: name of the pest, disease or weed, time of onset, name of the drug, dosage form, dosage, time, method and operator;

[0052] Harvesting information: harvesting date, harvesting base number, harvesting quantity, harvesting method, harvesting container, rapid testing information, and operating personnel.

[0053] Processing information:

[0054] Batch and sub-batch information: product name, original batch number, quantity and specification, and newly generated batch number;

[0055] Processed product identification: product name, batch number, quantity and specifications;

[0056] Process water information: process water quality information, disinfection method, and disinfectant dosage form;

[0057] Additive information: How to add.

[0058] Processing information: processing workshop, production line number, production date and time, operators;

[0059] Warehousing and logistics information:

[0060] Warehousing information: warehouse number, in and out quantity, time;

[0061] Logistics information: transport vehicle number, transport time, temperature and humidity records, and operator;

[0062] Inspection information: inbound and outbound inspection information.

[0063] (II) Determine different information collection plans for different key control points. Manual records should include text records and picture records; hardware information collection should use different hardware for different information. The specific collection methods are as follows:

[0064]

[0065] (III) Install 4K high-definition video surveillance equipment with night vision function in all links, and use large-scale cloud storage devices to realize cloud storage of information. The information can be stored for up to 2 years, covering the entire process of production, storage, circulation and trade of mainstream fruits.

[0066] Through the above three links, various links such as agricultural product production and circulation are connected to realize traceability verification of the entire industrial chain. Through traceability verification of the entire industrial chain, the problem of "broken chain" in traceability can be effectively solved, allowing consumers to distinguish between "false traceability" and "true traceability", and protecting the rights and interests of "true traceability" enterprises, thereby ensuring high-quality products and high prices.

[0067] The verification method provided by the present invention determines that the traceability information record of the enterprise is authentic and reliable only when the data of the three parties are completely consistent. The three parties jointly complete the provision of traceability information, which can avoid enterprise fraud, ensure that consumers see the most authentic data, realize the transparency of production information, guarantee consumers' right to know, and protect consumers' rights and interests.

[0068] Optionally, as an embodiment of the present invention, it also includes presenting a comparison of the traceability information of all parties when returning the traceability information to the consumer, and during the comparison, the consumer should be reminded of the permissible threshold value for each parameter.

[0069] Optionally, as an embodiment of the present invention, it also includes: when the comparison of the traceability information of the enterprise end and the management end is presented to the consumer, each traceability link of the management end can select one of the data collection devices for comparison.

[0070] Optionally, as an embodiment of the present invention, it also includes: if the final consumer still has doubts about the traceability information, the enterprise side or the management side can be warned to make corrections on their own.

[0071] Optionally, as an embodiment of the present invention, automatic verification may also be implemented, specifically including:

[0072] In response to the need for authenticity verification of a certain agricultural product, the traceability code of the agricultural product is obtained;

[0073] According to the traceability code of the agricultural product, inquiries are made at the enterprise end, management end, and monitoring end to obtain the traceability information of the agricultural product, the target parameters included in the traceability information, and the monitoring image.

[0074] Match the target parameters of the enterprise side and the management side;

[0075] Perform numerical comparison between successfully matched target parameters. Before numerical comparison, unify the unit and data type to determine whether the target parameter is a fixed value parameter or a tolerable parameter.

[0076] If it is a fixed value parameter, it is considered qualified only when the numerical comparison is completely consistent; if it is a tolerable parameter, it is considered qualified when the numerical difference does not exceed a preset percentage of one of the numerical values;

[0077] The target parameters that have not been successfully matched and whose value comparison fails are integrated into abnormal parameters;

[0078] The abnormal parameters and monitoring images are delivered to manual verification as automatic verification results.

[0079] Specifically, the demand for authenticity verification of a certain agricultural product can be a consumer scanning the QR code of the agricultural product, or the system can spontaneously perform self-verification. Through the unique traceability code, the corresponding traceability information can be obtained on the enterprise side, management side, and monitoring side. Fixed value parameters are determined values ​​such as "positioning information" and "quick test results". Generally, inconsistent fixed values ​​mean unequal information, and the degree of comparison is relatively strict; tolerable parameters are parameters such as "temperature" and "pH" that may have certain measurement errors. The tolerable parameters on the enterprise side and the management side allow for certain errors. In this embodiment, the error is 1% of one of the values.

[0080] Optionally, as an embodiment of the present invention, the correlation matching of the target parameters of the enterprise end and the management end includes: extracting the field name of the target parameter, creating a semantic matching model to determine whether the target parameters of the enterprise end and the management end match; the semantic matching model is a deep semantic matching model (Convolutional Latent Semantic Model, referred to as CLSM), the training sample includes two parameter field names in the traceability information as input, and manually annotated semantic similarity or dissimilarity results of the two parameter field names as output, and the semantic matching model is iteratively trained as new agricultural product varieties are added.

[0081] For example, the enterprise-side field name "pH" and the management-side field name "pH value" are semantically similar target parameters, which can be matched together and then compared in value.

[0082] Optionally, as an embodiment of the present invention, determining whether the target parameter is a fixed value parameter or a tolerable parameter includes: constructing an SVM classifier and training it using commonly used fixed value parameters and tolerable parameters; the SVM classifier input vector is the field name of the target parameter, and the output vector is the classification result of the fixed value parameter or the tolerable parameter.

[0083] Although the present invention has been described in detail by referring to the accompanying drawings and in combination with the preferred embodiments, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, a person of ordinary skill in the art may make various equivalent modifications or substitutions to the embodiments of the present invention, and these modifications or substitutions shall be within the scope of the present invention or any person skilled in the art may easily think of changes or substitutions within the technical scope disclosed by the present invention, and shall be within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A method for verifying the authenticity of agricultural product traceability, characterized in that: include: The "three-party verification" traceability verification system consists of traceability information from the enterprise side, management side, and monitoring side; Among them, the traceability information on the enterprise side includes: agricultural records and operation records directly entered and maintained by production enterprises; the traceability information on the management side includes real-time data directly uploaded by data collection devices in all traceability links and maintained by IoT suppliers; the traceability information on the monitoring side includes the real production videos of enterprises recorded by high-definition camera equipment in each traceability link of agricultural products; When obtaining the traceability verification requirements of consumers, the traceability information on the enterprise side is returned to the consumers; If the consumer has doubts about the traceability information on the enterprise side, the traceability information on the management side will be returned to the consumer, and the comparison of the traceability information on the enterprise side and the management side will be presented to the consumer; If the consumer still has doubts about the traceability information on the enterprise side, the traceability information on the monitoring side will be returned to the consumer, and the comparison between the enterprise side, management side, and monitoring side will be presented to the consumer; If consumers still have doubts about the authenticity of the traceability information, they can report it; Automatic verification can also be achieved, including: In response to the need for authenticity verification of a certain agricultural product, the traceability code of the agricultural product is obtained; According to the traceability code of the agricultural product, inquiries are made at the enterprise end, the management end, and the monitoring end to obtain the traceability information of the agricultural product, the target parameters included in the traceability information, and the monitoring image; Match the target parameters of the enterprise side and the management side; Perform numerical comparison between successfully matched target parameters. Before numerical comparison, unify the unit and data type to determine whether the target parameter is a fixed value parameter or a tolerable parameter. If it is a fixed value parameter, it is considered qualified only when the numerical comparison is completely consistent; if it is a tolerable parameter, it is considered qualified when the numerical difference does not exceed a preset percentage of one of the numerical values; The target parameters that have not been successfully matched and whose value comparison fails are integrated into abnormal parameters; The abnormal parameters and monitoring images are delivered to manual verification as automatic verification results.

2. The method according to claim 1, characterized in that Also includes: When the traceability information is returned to the consumer, a comparison of the traceability information of all parties is presented, and during the comparison, the consumer should be reminded of the permissible threshold for each parameter.

3. The method according to claim 1, characterized in that It also includes: when presenting the comparison of the traceability information on the enterprise side and the management side to consumers, each traceability link on the management side can select one of the data collection devices for comparison.

4. The method according to claim 1, characterized in that: Also includes: If the end consumer still has doubts about the traceability information, they can warn the enterprise or management to make corrections on their own.

5. The method according to claim 1, characterized in that The matching of the target parameters of the enterprise end and the management end includes: The field name of the target parameter is extracted, and a semantic matching model is created to determine whether the target parameters of the enterprise end and the management end match; the semantic matching model is a deep semantic matching model (Convolutional Latent Semantic Model, referred to as CLSM), and the training sample includes two parameter field names in the traceability information as input, and the semantic similarity or dissimilarity of the two parameter field names is manually annotated as output, and the semantic matching model is iteratively trained as new agricultural product varieties are added.

6. The method according to claim 1, characterized in that The step of determining whether the target parameter is a fixed value parameter or a tolerable parameter includes: Construct an SVM classifier and train it using commonly used fixed value parameters and tolerance parameters; The SVM classifier input vector is the field name of the target parameter, and the output vector is the classification result of the fixed value parameter or the tolerable parameter.

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