A whole-link peanut intelligent tracing system

Abstract

The application discloses a kind of full-link peanut intelligent tracing systems, belong to agricultural products intelligent tracing and quality safety management and control technical field, including full life cycle multidimensional data acquisition module, alliance chain tamper-proof storage module, peanut special quality risk early warning module, hierarchical authority data management module, multi-terminal intelligent tracing verification module, realize peanut full production circulation link data automation, standardization acquisition by Internet of Things technology, rely on alliance chain double encryption storage technology, solve the problem that traditional tracing data is easy to tamper with, poor public credibility;While innovatively build peanut special quality risk threshold model, solve peanut mildew, aflatoxin breeding, pesticide residue overproof and other special quality hidden danger, realize from after-tracing to early warning, in-process control upgrade;Build three-level authority multi-terminal application system, adapt enterprise production operation and maintenance, government accurate supervision, multiple scene needs of consumer convenient verification, have broad industrialization application prospect.

Description

Technical Field

[0001] This invention relates to the field of intelligent traceability and quality and safety control technology for agricultural products, specifically to a full-chain intelligent traceability system for peanuts covering the entire life cycle of peanut planting, harvesting and sorting, processing, warehousing, cold chain logistics and terminal sales. It is applicable to scenarios such as full-process traceability and evidence storage for oil crops, dedicated quality risk early warning, precise government supervision and consumer authenticity verification. Background Technology

[0002] Peanuts are a core oilseed crop and a distinctive economic crop in my country, widely used in edible oil pressing, snack food processing, and the production of agricultural by-products. Their quality and safety are directly related to the health of the nation's diet and the standardized development of the grain and oil industry. With the popularization of agricultural product traceability systems, existing peanut traceability technologies are gradually being implemented, but significant shortcomings still exist in terms of professionalism, intelligence, safety, and closed-loop management.

[0003] Existing peanut traceability systems generally suffer from four core defects: fragmented traceability links, poor scenario adaptability, low data credibility, and lack of risk control. Firstly, traditional traceability systems mostly rely on post-processing data entry, covering only the processing and sales stages. They fail to achieve end-to-end data connectivity from the field to the consumer, lacking crucial quality-influencing data such as planting environment, agricultural operations, and cold chain storage. When quality issues like mold or excessive pesticide residues occur, the traceability nodes cannot be accurately located. Secondly, traditional systems employ a centralized data storage model, allowing for manual alteration, addition, and deletion of data. This lack of credibility in traceability information fails to meet the needs of judicial evidence preservation and market supervision.

[0004] Crucially, peanuts possess unique quality characteristics distinct from ordinary fruits and vegetables: they are highly susceptible to aflatoxin growth due to temperature and humidity fluctuations, prone to mold growth during storage, and pose a significant risk of pesticide residues. Existing general-purpose agricultural product traceability systems lack a peanut-specific risk assessment model, only providing basic information disclosure and failing to enable real-time monitoring, early warning, and closed-loop management of core peanut quality risks. Furthermore, traditional systems suffer from vague permission divisions and limited verification methods, failing to meet the diverse needs of enterprise production control, government compliance supervision, and rapid consumer verification. The industry urgently requires a targeted, tamper-proof, early warning-enabled, end-to-end intelligent traceability system specifically for peanuts. Summary of the Invention

[0005] This invention addresses the shortcomings of existing peanut traceability technologies, such as incomplete traceability links, susceptibility to data tampering, lack of crop-specific risk warnings, low control precision, and poor multi-level adaptability. It provides a full-chain intelligent peanut traceability system. This invention aims to achieve automatic multi-dimensional data collection throughout the peanut lifecycle, tamper-proof blockchain-based evidence storage, intelligent early warning of peanut-specific quality risks, multi-level terminal hierarchical control, and visualized traceability verification. It constructs a closed-loop intelligent control system encompassing data collection, evidence storage, early warning, disposal, and traceability, comprehensively improving the accuracy of peanut product quality and safety control and the credibility of traceability.

[0006] To achieve the above objectives, this invention provides the following technical solution: a full-chain intelligent peanut traceability system, comprising five core functional modules: a full lifecycle multi-dimensional data acquisition module, a consortium blockchain anti-tampering evidence storage module, a peanut-specific quality risk early warning module, a hierarchical permission data management module, and a multi-terminal intelligent traceability verification module. Each module interacts bidirectionally with data and operates collaboratively to form a fully closed-loop traceability and control system.

[0007] The full lifecycle multidimensional data acquisition module communicates and connects in real time with the hierarchical permission data management module, fully covering six major business scenarios: peanut planting, harvesting and sorting, processing, warehousing, logistics, and terminal sales. It integrates three acquisition methods: automatic acquisition via the Internet of Things, full-process image recording, and standardized manual supplementation, to achieve full-dimensional and uninterrupted acquisition of environmental parameters, agricultural data, process parameters, quality inspection data, and logistics and sales data, ensuring the integrity of traceability data from the source.

[0008] The consortium blockchain's tamper-proof evidence storage module communicates and interfaces in real time with the hierarchical access control data management module. Employing a consortium blockchain distributed storage architecture and national cryptographic algorithms, it cleans, hashes, encrypts, and timestamps various types of traceability data collected in real time, enabling real-time on-chain evidence storage. Each batch of peanuts is bound to a unique batch identifier and a one-item-one-code traceability QR code. All on-chain data is chain-linked, tamper-proof, and fully traceable, possessing judicial evidentiary value and completely resolving the data forgery problem inherent in traditional centralized storage.

[0009] The peanut-specific quality risk early warning module communicates and interfaces in real time with the hierarchical access control data management module. It incorporates an adaptive risk threshold model tailored to the growth and storage characteristics of peanuts, specifically addressing four key quality risks: excessive pesticide residues, high-temperature mold growth, aflatoxin proliferation in high humidity, and spoilage due to cold chain failure. By comparing real-time monitoring data with national standard thresholds and crop-specific thresholds, it automatically identifies potential quality hazards, triggers multi-level warnings, and marks risky batches, achieving a technological upgrade from post-event traceability to pre-event warning and in-process control.

[0010] The hierarchical access control data management module connects to the other four modules: the enterprise operation unit, the administrative supervision unit, and the public inquiry unit, enabling traceability data to be categorized and stored, batch-related, compliantly corrected, and with access control isolated. It also incorporates a national peanut quality and safety standard library and a standardized process parameter library, providing standard support for risk assessment, quality verification, and data calibration.

[0011] The multi-terminal intelligent traceability and verification module includes three types of terminal carriers: enterprise management terminal, government regulatory terminal, and consumer mobile terminal, adapting to different user scenarios. The enterprise management terminal realizes risk handling, batch control, and data operation and maintenance; the government regulatory terminal realizes data evidence collection, compliance verification, and responsibility tracing; and the consumer mobile terminal realizes visualized full-chain traceability and rapid verification of product authenticity.

[0012] Furthermore, the full lifecycle multidimensional data acquisition module includes an IoT sensing unit, a panoramic image acquisition unit, and a standardized data entry unit. The IoT sensing unit is deployed in planting bases, warehouses, and cold chain transportation equipment to automatically collect soil temperature and humidity, pH value, air temperature and humidity, transportation temperature and humidity, and meteorological parameters. The panoramic image acquisition unit records images of peanut operations throughout their entire lifecycle. The standardized data entry unit standardizes the entry of agricultural operations, quality inspection reports, and batch information, avoiding the problems of messy manual entry and missing data.

[0013] Furthermore, the consortium blockchain anti-tampering evidence storage module adopts a dual encryption mechanism combining RSA asymmetric encryption and SHA-256 hash encryption. Each block of data is uniquely bound to a timestamp, a unique device code, a product batch code, and a unique hash value. The block data is verified layer by layer and locked in a chain, supporting judicial platform integration for evidence collection and preventing data tampering, batch forgery, and information supplementation violations.

[0014] Furthermore, the multi-terminal intelligent traceability verification module adopts a time-axis visual traceability display mode, which fully displays the traceability information of peanuts throughout their entire life cycle according to the production time sequence, highlights and marks risky and abnormal data in pop-up windows, and automatically displays compliance and qualification marks for risk-free batches, so as to make the traceability results intuitive and clear.

[0015] Furthermore, all early warning records, risk handling records, and re-inspection and rectification records of the peanut-specific quality risk early warning module are simultaneously uploaded to the blockchain for archiving, forming a closed-loop management ledger for monitoring, early warning, handling, review, and archiving, so as to make risk issues traceable, rectification processes verifiable, and responsible parties identifiable.

[0016] Furthermore, the peanut-specific quality risk threshold model adopts a national standard fixed threshold plus scenario adaptive fine-tuning mode, aligns with the national standards GB 2762 and GB 2763, automatically matches the pesticide residue limit standards for peanuts from different production areas and varieties, improves the accuracy of risk identification, and determines that exceeding the threshold is a high risk of mold and aflatoxin growth.

[0017] The advantages of this invention are: This invention is the first of its kind to create a closed-loop traceability system for peanuts, breaking through the limitations of traditional single-link traceability. It fully covers six core production and sales scenarios for peanuts, breaks down data barriers between links, and achieves seamless data flow throughout the entire lifecycle from the field source to the terminal market, solving industry pain points such as broken traceability links, fragmented data, and difficulty in locating problems.

[0018] This invention addresses the specific quality risks associated with peanuts. Unlike general agricultural product traceability systems, this invention establishes a peanut-specific risk assessment model that precisely adapts to the characteristics of peanuts, such as susceptibility to mold, aflatoxin contamination, and significant pesticide residue risks. This enables pre-emptive warnings and in-process control of quality risks, significantly reducing product non-compliance rates compared to traditional post-event traceability models.

[0019] This invention provides multi-level permission adaptation for applications across all scenarios, constructing a three-level permission isolation system that takes into account the needs of enterprise production control, government supervision, and convenient verification for consumers. It is suitable for use by multiple entities, including large-scale enterprises, small and medium-sized cooperatives, regulatory departments, and end users, and has strong versatility and practicality.

[0020] This invention is highly automated and easily implemented: it integrates automatic data collection via the Internet of Things with standardized manual data entry, reducing manual intervention and data entry errors. It is adaptable to the needs of peanut planting, processing, and sales entities of different scales and can be rapidly promoted and applied on a large scale. Attached Figure Description

[0021] Figure 1 This is a block diagram of the overall architecture of the end-to-end intelligent peanut traceability system provided in this embodiment of the invention; Figure 2 This is a schematic diagram of the complete process of end-to-end data collection, encrypted on-chain processing, and traceability verification provided in the embodiments of the present invention. Detailed Implementation

[0022] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0023] This embodiment represents the optimal deployment solution for large-scale integrated peanut planting and processing enterprises. The system is based on a cloud-based Linux server architecture and is equipped with IoT data acquisition hardware, a web management backend, a dedicated monitoring terminal, and a consumer mini-program terminal to achieve intelligent traceability and risk control throughout the entire process. The specific implementation steps are as follows: S1. Hardware Deployment and System Initialization: Soil sensors, meteorological monitoring terminals, and high-definition infrared cameras are deployed in large-scale peanut planting bases, with a data collection frequency of 10 minutes / time. High-precision temperature and humidity monitoring terminals are deployed in constant-temperature storage warehouses, with a data collection frequency of 5 minutes / time. Beidou positioning and vehicle-mounted temperature and humidity recorders are deployed on cold chain logistics vehicles. The system backend inputs GB2762 and GB 2763 national quality standards, solidifies peanut-specific risk thresholds and standardized process parameters, and completes the configuration of three-level access accounts and the initialization of encrypted parameters.

[0024] S2. Synchronous Data Collection Across All Dimensions: During the planting stage, soil, meteorological, and growth environment data are automatically collected, and agricultural operations are recorded in images. Fertilization and pesticide application details are entered manually in a standardized manner. During the harvesting and sorting stage, data on harvest yield, sorting grade, and damage rate are entered by linking the planting plots to batches. During the processing stage, the system connects to automated production lines, collects process parameters such as roasting, pressing, and sterilization in real time, and uploads third-party quality inspection reports. During the warehousing and cold chain stage, environmental temperature and humidity, transportation trajectory, and cold chain status are monitored around the clock. During the sales stage, batch outbound, distributor, and shelf information are entered, achieving closed-loop data collection across the entire supply chain.

[0025] S3. Blockchain Encrypted On-Chain Evidence Storage: The system cleans and standardizes the collected multi-source data, generating unique encrypted values ​​through RSA asymmetric encryption combined with SHA-256 hash encryption. These values ​​are then bound to timestamps, device codes, and batch codes before being uploaded to the consortium blockchain in real time, generating tamper-proof block data. Simultaneously, a unique traceability QR code is generated for each batch of products, achieving "one code per batch, one traceability per item." All data is permanently stored on the blockchain, ensuring a complete record.

[0026] S4. Exclusive Intelligent Risk Early Warning and Closed-Loop Management: The system uses a risk threshold model to compare data in real time. When the storage temperature and humidity exceed preset thresholds, it automatically determines the risk of mold and aflatoxin growth; when agricultural pesticide data exceeds national standard residue thresholds, it determines the risk of pesticide residue exceeding standards. After an early warning is triggered, the system simultaneously completes background pop-ups, mobile push notifications, and highlights the risk batches. Staff promptly complete batch isolation, re-inspection, and rectification. All disposal data is synchronously uploaded to the blockchain and archived, forming a closed-loop risk management system.

[0027] S5, Multi-level Terminal Traceability Application: Enterprise management end realizes full batch data monitoring, risk handling and production operation and maintenance; government regulatory end retrieves original blockchain evidence data to carry out compliance verification and responsibility traceability; consumers can scan the code to view the full process traceability information, quality inspection reports and risk records through timeline visualization, and quickly complete the authenticity and quality verification.

[0028] S6. Long-term data archiving: After the product circulation is completed, the system automatically archives all batch data and stores it on the blockchain node for a long time, providing data support for production optimization, quality upgrading and industry data analysis.

[0029] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A full-chain intelligent traceability system for peanuts, characterized in that: It includes a full lifecycle multi-dimensional data collection module, a consortium blockchain anti-tampering evidence storage module, a peanut-specific quality risk early warning module, a hierarchical permission data management module, and a multi-terminal intelligent traceability and verification module; The full lifecycle multidimensional data acquisition module is used to collect full-dimensional production, environmental, quality inspection, and circulation traceability data; The consortium blockchain anti-tampering evidence storage module is connected in real time to the full lifecycle multi-dimensional data acquisition module. It is used to perform double encryption, hash operation, and real-time on-chain storage on the collected traceability data to generate a unique batch traceability identifier and traceability QR code. The peanut-specific quality risk early warning module has a built-in adaptive risk threshold model adapted to the characteristics of peanut crops. It is used to specifically monitor four major quality risks of peanuts: excessive pesticide residues, high temperature mold, high humidity aflatoxin growth, and cold chain failure and deterioration, so as to achieve automatic risk identification and multi-level early warning. The hierarchical permission data management module is used to construct a three-level permission isolation unit to complete the classification and storage of traceability data, batch association, standard calibration and compliance management; The multi-terminal intelligent traceability and verification module includes an enterprise management terminal, a government regulatory terminal, and a consumer mobile terminal, which are used to realize multi-scenario adaptation applications for enterprise production control, government compliance supervision, and public traceability and verification.

2. The end-to-end intelligent peanut traceability system according to claim 1, characterized in that: The full lifecycle multidimensional data acquisition module includes an IoT sensing unit, a panoramic image acquisition unit, and a standardized data recording unit. The IoT sensing unit is used to automatically collect soil parameters, meteorological parameters, storage temperature and humidity, cold chain transportation temperature and humidity, and location data. The panoramic image acquisition unit is used to record images of the entire peanut production process throughout its entire lifecycle. The standardized data recording unit is used to standardize the entry of agricultural operations, quality inspection reports, and batch circulation text data.

3. The end-to-end intelligent peanut traceability system according to claim 1, characterized in that: The consortium blockchain anti-tampering evidence storage module adopts a dual encryption mechanism of RSA asymmetric encryption combined with SHA-256 hash encryption. Each block of data is uniquely bound to a timestamp, a unique device code, a product batch code, and a unique hash value.

4. The end-to-end intelligent peanut traceability system according to claim 1, characterized in that: The multi-terminal intelligent traceability and verification module adopts a time-series visualization display method, presenting the entire life cycle traceability process of peanuts in a timeline, highlighting risky and abnormal data, and automatically displaying quality qualified marks for compliant batches.

5. The end-to-end intelligent peanut traceability system according to claim 1, characterized in that: The hierarchical access control data management module includes three levels of access control units: enterprise operation unit, administrative supervision unit, and public inquiry unit, which are used to achieve hierarchical control of data security. The enterprise management terminal is used for data entry, rectification and maintenance, the government supervision terminal is used for verification, evidence collection and accountability, and the consumer mobile terminal is used for public information inquiry.

6. The end-to-end intelligent peanut traceability system according to claim 1, characterized in that: The early warning records, batch isolation records, and rectification and review records of the peanut-specific quality risk early warning module are all synchronously archived on the blockchain, forming a closed-loop risk control ledger.

7. The end-to-end intelligent peanut traceability system according to claim 1, characterized in that: The peanut-specific quality risk early warning module has a built-in peanut-specific quality risk threshold model. The model adopts a national standard fixed threshold combined with a scenario-adaptive fine-tuning mode. It has a built-in standard threshold to adaptively adjust the discrimination parameters according to the peanut production area and variety, identify quality risks and automatically trigger early warnings.

Images