Breeding data management method and system based on block chain

Abstract

The invention discloses a breeding data management method and system based on a block chain. The breeding data management method based on the block chain comprises the following steps: in a data acquisition and preprocessing stage, inputting acquired breeding data into a data center through Internet of Things equipment, and carrying out standardization processing on the breeding data; in a data uplink and storage stage, calculating a Hash value for qualified data, and writing the Hash value into an alliance chain after passing consensus verification; in the data sharing and using stage, data ownership registration, sharing authorization and quality verification are carried out through the intelligent contract module. According to the method, the breeding data of multiple subjects can be managed, the breeding research efficiency is improved, the commercial confidential safety of each subject is guaranteed, and the breeding data of each subject can obtain data sharing benefits through the alliance chain.

Description

A blockchain-based method and system for breeding data management Technical Field

[0001] This invention relates to the field of data management technology, and in particular to a method and system for breeding data management based on blockchain. Background Technology

[0002] At this critical stage of the transformation of intelligent breeding from experimental selection to computational selection, the precise management, secure sharing, and efficient utilization of breeding data have become the core bottlenecks restricting breakthroughs in the seed industry.

[0003] Traditional breeding databases are either limited to a simple compilation of laboratory and field data, or they lose their collaborative value due to the "data silo" problem. Breeding data from different entities cannot be effectively exchanged and integrated, resulting in duplicated experiments among different entities and limiting the efficiency of breeding research. Summary of the Invention

[0004] This invention provides a blockchain-based breeding data management method and system to manage breeding data from multiple entities, avoid redundant experiments, improve breeding research efficiency, protect the commercial secrets of each entity, and enable each entity to benefit from data sharing through a consortium blockchain.

[0005] In a first aspect, embodiments of the present invention provide a blockchain-based breeding data management method, comprising: in the data acquisition and preprocessing stage, inputting acquired breeding data into a data center via an IoT device and performing standardized processing on the breeding data; in the data on-chain and storage stage, calculating hash values ​​for qualified data, verifying them through consensus, and writing them into a consortium blockchain; in the data sharing and usage stage, registering data ownership, authorizing sharing, and verifying quality through a smart contract module; wherein, the data center is used to store and manage the breeding data through a distributed file storage system, and the breeding data includes genotype data, phenotypic data, and environmental data; the consortium blockchain consists of multiple authorized nodes, each with a corresponding scope of permissions; the consortium blockchain is used to store the hash value, ownership certificate, and sharing authorization information of each piece of breeding data; the data center and the consortium blockchain are associated with the breeding data through a core data index; the smart contract module is deployed on the consortium blockchain, and the smart contract module is used to register data ownership, authorize sharing, and verify quality of the breeding data.

[0006] Optionally, the method further includes: providing full lifecycle data traceability query and real-time monitoring through the application layer during the data traceability and supervision phase.

[0007] Optionally, the data acquisition and preprocessing stage specifically includes: inputting the collected breeding data into the data center via IoT devices and manual input, and performing preliminary filtering by edge computing nodes; performing standardized format conversion on the breeding data in the data center and supplementing metadata to generate a temporary ID; triggering a data quality smart contract to automatically detect and score the breeding data according to preset indicators, and allowing only qualified breeding data to enter the next stage.

[0008] Optionally, the consortium blockchain includes a main chain and side chains; the side chains are divided into genotype side chains, phenotype side chains, and environment side chains, and each side chain interacts with the main chain through a cross-chain communication protocol; the data on-chain and storage stage further includes: managing the ownership of the breeding data and the node identity of the authorized nodes through the main chain.

[0009] Optionally, the cross-chain communication protocol adopts a hash locking and smart contract verification mechanism; the permission scope of each authorized node is dynamically adjusted based on data contribution and reputation value; the block structure of the sidechain includes a spatiotemporal tag field, and the data on-chain and storage stage further includes: recording the spatial coordinates, time period and environment number of the breeding test field corresponding to the breeding data through the spatiotemporal tag field, and the spatiotemporal tag field supports data association query based on spatiotemporal dimension.

[0010] Optionally, the smart contract module includes: a data ownership contract for registering the creator information of the breeding data and generating an ownership certificate; a data sharing contract for automatically verifying user permissions and executing point-based incentive settlement; a data quality contract for scoring the quality of the uploaded breeding data; and a regulatory audit contract for recording the operation logs of the breeding data and detecting violations. During the data sharing and usage phase, the module further includes: registering the creator information of the breeding data and generating an ownership certificate through the data ownership contract; automatically verifying user permissions and executing point-based incentive settlement through the data sharing contract; scoring the quality of the uploaded breeding data through the data quality contract; and recording the operation logs of the breeding data and detecting violations through the regulatory audit contract.

[0011] Secondly, embodiments of the present invention also provide a blockchain-based breeding data management system, which is used to implement the blockchain-based breeding data management method described in any embodiment of the present invention. The blockchain-based breeding data management system includes a data center, a consortium blockchain, and a smart contract module.

[0012] Optionally, the blockchain-based breeding data management system further includes, in sequence, a bottom protocol layer, an infrastructure layer, a blockchain framework layer, a data layer, a contract layer, a business layer, a functional layer, and an application layer; the bottom protocol layer is used to define the communication and security protocols between the data center and the consortium blockchain; the infrastructure layer consists of the hardware devices of the data center, the consortium blockchain, and the smart contract module; both the blockchain framework layer and the data layer are located in the data center, and the blockchain framework layer is used to manage the breeding data; the data layer is used to store the breeding data through a distributed file storage system; the contract layer is used to set the data ownership contract, the data sharing contract, the data quality contract, and the regulatory audit contract in the smart contract module.

[0013] Optionally, the business layer includes a germplasm resource management module, a breeding experiment management module, a data sharing management module, and a variety approval management module. The germplasm resource management module is used for the storage, preservation, propagation, updating, and release of germplasm resources for various crops. The breeding experiment management module is used to connect to edge computing devices, collect field data in real time, and associate the genotype data and environmental data in the breeding data to generate experiment reports. The data sharing management module is used to provide a convenient entry point for data sharing and acquisition. The variety approval management module is used to complete the approval process for the breeding data.

[0014] Optionally, the application layer provides three application forms: a web platform, a mobile app, and an API interface, and connects with third-party systems through RESTful interfaces.

[0015] This invention provides a blockchain-based breeding data management method and system. During the data acquisition and preprocessing stage, breeding data is input into a data center via IoT devices and standardized. This allows various entities to upload breeding data to the blockchain through authorized nodes, enabling collaborative management by multiple institutions. In the data uploading and storage stage, hash values ​​are calculated for qualified data, and after consensus verification, the data is written to the consortium blockchain. In the data sharing and usage stage, a smart contract module handles data ownership registration, sharing authorization, and quality verification. The consortium blockchain stores the hash value, ownership certificate, and sharing authorization information for each breeding data point. The data center and the consortium blockchain are linked through a core data index. The smart contract module, deployed on the consortium blockchain, is used for data ownership registration, sharing authorization, and quality verification, thereby achieving data sharing. This invention enables the management of breeding data from multiple entities, avoiding redundant experiments, improving breeding research efficiency, protecting the commercial secrets of each entity, and allowing each entity to benefit from data sharing through the consortium blockchain. Attached Figure Description

[0016] Figure 1 is a flowchart of a blockchain-based breeding data management method provided in an embodiment of the present invention; Figure 2 is a structural diagram of a blockchain-based breeding data management system provided in an embodiment of the present invention; Figure 3 is a schematic diagram of a consortium blockchain provided in an embodiment of the present invention; Figure 4 is a flowchart of another blockchain-based breeding data management method provided in an embodiment of the present invention; Figure 5 is a flowchart of the workflow of a blockchain-based breeding data management system provided in an embodiment of the present invention. Detailed Implementation

[0017] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0018] At this critical stage of the transformation of intelligent breeding from "experimental selection" to "computational selection," the precise management, secure sharing, and efficient utilization of breeding data have become core bottlenecks restricting breakthroughs in the seed industry. Traditional breeding databases are either limited to simple accumulations of laboratory and field data or lose their collaborative value due to the "data silo" problem. Blockchain technology, with its decentralized, tamper-proof, traceable, and automated smart contract execution characteristics, provides a revolutionary solution to this dilemma.

[0019] However, while the fully decentralized nature of public blockchains can ensure data openness and transparency, they also suffer from low transaction efficiency (only a few to dozens of transactions per second), weak data privacy protection, and high energy consumption, which cannot meet the needs of large-capacity storage and highly sensitive protection of breeding data. Private blockchains, controlled by only a single entity, can ensure data security, but are essentially still a "centralized" architecture, unable to solve the "data silo" problem, and run counter to the collaborative needs of intelligent breeding.

[0020] To address the problems in the existing technology, this invention also provides a blockchain-based breeding data management method, which realizes trusted management of breeding data throughout its entire lifecycle from collection, storage, sharing to application, providing solid data infrastructure support for intelligent breeding. Figure 1 is a flowchart of a blockchain-based breeding data management method provided by this invention. As shown in Figure 1, the blockchain-based breeding data management method includes: S110, in the data collection and preprocessing stage, the collected breeding data is entered into the data center through an Internet of Things device, and the breeding data is standardized.

[0021] S120. During the data on-chain and storage phase, the hash value of qualified data is calculated and written into the consortium blockchain after consensus verification.

[0022] S130. During the data sharing and usage phase, data ownership registration, sharing authorization, and quality verification are carried out through the smart contract module.

[0023] Specifically, in the data acquisition and preprocessing stage, multi-source data acquisition is required. Breeding data is input into the data center via IoT devices. For example, breeding companies and research institutions collect environmental and phenotypic data through IoT devices (sensors, drones, etc.), genotypic data through laboratory equipment, and manually supplement data such as experimental design and field management. The breeding data undergoes preliminary filtering through edge computing nodes to remove obvious noise before being transmitted to the data center. Then, the breeding data undergoes standardization processing. This standardization may involve the data center calling a data processing module to convert the acquired breeding data to conform to the database's standardized format; simultaneously, data metadata (source, acquisition device, time, etc.) is added, and a unique temporary ID is assigned to each data point. Furthermore, data quality testing is performed. The data center triggers a data quality contract, which automatically tests the data according to preset indicators, generating a data quality score and test report. Unqualified data is returned to the authorized entity for correction, while qualified data proceeds to the next stage.

[0024] Data preprocessing can also include data cleaning, outlier detection, and missing value completion. For potential observational errors in phenotypic data, the "3σ criterion" is used to identify outliers, which are then corrected using the mean values ​​of the same plot and growth period. For sequencing errors in genotypic data, correction is performed by comparing with a reference genome. For missing values ​​in environmental data, time series prediction models (such as LSTM) are used for completion. Preprocessed datasets must pass data quality checks, and only those achieving an accuracy of 99.5% or higher can proceed to the blockchain process. Format standardization: Genotypic data uses VCF (Variant Call Format), phenotypic data uses CSV format with clearly defined fields (e.g., plant height in cm, yield in kg / acre), and environmental data uses JSON format with internationally recognized meteorological and soil classification codes. Furthermore, to ensure data traceability, each data entry must include three core metadata fields: "Data Source (Institution / Individual)," "Collection Device Number," and "Data Generation Time." Hash Calculation: A "double hashing" mechanism is employed to ensure data uniqueness and security. First, the original data is hashed using the SHA-256 algorithm. Then, this hash value is further encrypted using the data owner's private key, generating the final "data fingerprint." This "data fingerprint" is stored in the block as part of the core data index. Any modification to the original data will cause a change in the "data fingerprint," allowing for rapid identification by blockchain nodes and ensuring data immutability.

[0025] During the data on-chain and storage phase, hash values ​​are calculated for qualified data. The data center uses a "double hashing" mechanism to calculate data fingerprints for qualified data, and simultaneously generates a core data index (containing information such as data ID, type, and storage location). Authorized entities collecting data submit data on-chain applications through the business layer, triggering a data ownership contract. The contract records data ownership information and generates an ownership certificate. The data center can package the core data index, data fingerprint, and ownership information into a transaction request and send it to the authorized nodes of the consortium blockchain. After receiving the transaction request, the authorized nodes of the consortium blockchain verify it through a "PBFT+PoS" hybrid consensus mechanism. After successful verification, the block management module writes the transaction data into a new block. The block is linked to the previous block through a chain structure and simultaneously synchronized to all authorized nodes within the consortium blockchain. Tiered storage: The core data index and transaction data are stored in the authorized nodes of the consortium blockchain. The original breeding data is categorized according to "shared attributes" and stored in the data center's distributed storage system (shared data) or enterprise local storage (confidential data). The data center uses index mapping to link on-chain and off-chain data.

[0026] Considering the characteristics of consortium blockchains, a hybrid consensus mechanism of "Practical Byzantine Fault Tolerance (PBFT) + Proof-of-Stake (PoS)" is adopted. PBFT ensures transaction consistency and security by verifying the legitimacy of data upload through multiple rounds of voting among nodes, achieving a fault tolerance rate of 1 / 3. PoS adjusts node weights by incorporating a node's "data contribution" and "reputation value" into the weight calculation. Nodes with larger data contributions and higher reputation values ​​(such as large seed companies and authoritative research institutions) have higher voting weights, encouraging data sharing while ensuring consensus efficiency. After successful consensus verification, the data is officially written to the block and synchronized to all nodes in the consortium, completing the on-chain process.

[0027] During the data sharing and usage phase, data ownership registration, sharing authorization, and quality verification are conducted through a smart contract module. Specifically, this includes: the owner of breeding data publishes shared data through the application layer platform, sets sharing rules (permission level, usage fee, duration, etc.), triggers a data sharing contract, and the contract writes the sharing information to the blockchain; users filter data according to their needs through the application layer platform's query module, and the platform quickly locates the target data through on-chain indexes; users submit data usage applications, specifying the purpose and permission requirements; the data sharing contract automatically verifies the user's identity, account points (or balance), and data sharing rules, generating an authorization certificate upon approval, which is synchronized to the user and the data center; data acquisition and usage: users retrieve the original breeding data through the data center using the authorization certificate, and the data center records usage logs and synchronizes them to the blockchain; users use the data within the authorized scope (e.g., analysis, research), and if they need to exceed the authorized scope (e.g., secondary sharing), they must resubmit an application and pass contract verification; incentives and settlement: the data sharing contract automatically transfers the user's payment (or points) to the data owner's account according to preset rules and records transaction details; the data owner's points can be used to redeem other data or platform services, forming an incentive loop for data sharing.

[0028] This invention also provides a blockchain-based breeding data management system, employing a hybrid architecture of a data center and a consortium blockchain. By constructing a breeding data management system adapted to the characteristics of breeding data, it achieves trusted management of the entire lifecycle of breeding data from collection, storage, sharing to application, providing solid data infrastructure support for intelligent breeding. Figure 2 is a schematic diagram of the structure of a blockchain-based breeding data management system provided by this invention. As shown in Figure 2, the blockchain-based breeding data management system includes a data center 110, a consortium blockchain 120, and a smart contract module 130.

[0029] Data center 110 is used to store and manage breeding data through a distributed file storage system. The breeding data includes genotype data, phenotypic data, and environmental data.

[0030] The consortium blockchain 120 consists of multiple authorized nodes, each with its own scope of permissions. The consortium blockchain 120 is used to store the hash value, ownership certificate, and shared authorization information of each breeding data. The data center 110 is linked to the consortium blockchain 120 through a core data index.

[0031] The smart contract module 130 is deployed on the consortium blockchain 120. The smart contract module 130 is used to register data ownership, authorize sharing, and verify the quality of breeding data.

[0032] In this embodiment of the invention, the data center 110 can undertake the core responsibilities of large-capacity storage and efficient computing. On the one hand, the data center 110 can store the original breeding data through the Hadoop Distributed File System (HDFS). On the other hand, the data center 110 can deploy big data analysis engines, such as Spark and Flink, to provide breeders with computing services such as phenotypic prediction and gene mapping, and realize the management of breeding data. The calculation results and core parameters of the data center 110 can be synchronized to the consortium blockchain 120 to ensure that the calculation process is traceable.

[0033] Breeding data, as data generated during the breeding process, is a typical multi-dimensional, highly sensitive, and strongly correlated composite data, and its characteristics impose clear requirements on its architecture design. From a dimensional perspective, breeding data encompasses genotypic data (genome sequences, molecular markers, gene expression levels, etc.), phenotypic data (field observation data such as plant height, yield, and disease resistance), and environmental data (spatial and temporal dynamic data such as soil fertility, meteorological data, and irrigation conditions). A single breeding data point represents the data generated during the breeding process of a single breeding material; the complete data chain for a single breeding material can reach hundreds of gigabytes in size and must support multi-dimensional cross-queries. From a sensitivity perspective, genotypic data of core breeding materials, proprietary hybridization schemes, and field trial results are all considered trade secrets, directly impacting a company's core competitiveness. Some germplasm resource data related to food security must also comply with regulatory requirements, necessitating extremely high privacy protection standards. From a correlation perspective, phenotypic data is the result of the combined effects of genotype and environmental factors; the realization of the data's value depends on deep correlation analysis among these three factors, requiring an architecture that supports efficient data correlation across subjects and time periods. In addition, the original breeding data can include large-volume unstructured data such as high-definition phenotypic images, whole genome sequencing data, and continuous meteorological monitoring data. Data center 110 stores the original breeding data through HDFS, which solves the problems of on-chain data redundancy and low transaction efficiency caused by directly storing large-volume data on the blockchain.

[0034] In this embodiment of the invention, the consortium blockchain 120 can be jointly managed by multiple authorized entities. Through a node admission mechanism, it achieves "controllable decentralization," retaining the trustworthiness of blockchain while improving efficiency through a customized consensus mechanism, thus adapting to the specific needs of breeding data. The consortium blockchain 120 consists of multiple authorized nodes, each with its own scope of authority and authorized entity. Each authorized entity manages one or more authorized nodes. For example, Figure 3 is a schematic diagram of the consortium blockchain provided in this embodiment. As shown in Figure 3, authorized entity A can manage authorized nodes A1 and A2, authorized entity B can manage authorized nodes B1 and B2, and authorized entity C can manage authorized node C. Authorized nodes A1, A2, B1, B2, and C are interconnected to form a distributed network, constituting the consortium blockchain 120. In this embodiment, the authorized entity refers to breeding institutions, such as seed companies, research institutes, and agricultural colleges. Furthermore, the authorized entity also includes regulatory departments, enabling them to monitor the flow of germplasm resources and the use of breeding data in real time through the authorized nodes, thereby ensuring national seed industry security. In addition, each authorized node can have a corresponding data center 110 to store the original breeding data.

[0035] In this embodiment of the invention, a node identity authentication mechanism allows authorized entities such as seed companies, research institutes, agricultural colleges, and government regulatory departments to be incorporated into the consortium blockchain 120. Each authorized entity manages one or more authorized nodes, and each authorized node possesses an independent identity certificate and scope of permissions, ensuring the controllability of data sharing. The consortium blockchain 120 can also utilize the immutability of blockchain to store the hash value, ownership certificate, and sharing authorization information for each breeding data entry. Each piece of breeding data has a unique hash value and timestamp, recording key information such as the data creator, modification history, and sharing scope, thereby resolving issues such as unclear ownership and the risk of tampering with breeding data. The smart contract module 130 is deployed on the consortium blockchain 120. The smart contract module 130 can register data ownership, authorize sharing, and verify the quality of breeding data. Ownership registration clarifies the ownership and change rules of the breeding data. Sharing authorization defines the sharing rules for breeding data, such as the sharing scope, usage period, and fee standards for different types of breeding data. Quality verification uses a preset quality detection algorithm to test the reliability of uploaded breeding data, ensuring its quality. The smart contract module 130 enables automated authorization and incentives for breeding data sharing, allowing authorizing entities to earn revenue from their own breeding data. For example, companies can obtain data points after sharing breeding data, which can be used to redeem shared data or platform services from other authorizing entities. This breaks down the barriers to profit formed by data silos and promotes the progress and development of the breeding industry.

[0036] Furthermore, data center 110 and consortium blockchain 120 are linked through a core data index to connect breeding data. The core data index serves as a crucial link between consortium blockchain 120 and data center 110. It does not store the breeding data itself, but only unique index information for the breeding data within the data center, including data ID, data type (labeled as genotype data / phenotypic data / environmental data / calculation results, etc.), data size (facilitating rapid data location by data center 110), and storage node address (recording the storage location of the breeding data in the distributed data center). The data ID can use UUID format to ensure uniqueness. Through the core data index, authorized nodes of consortium blockchain 120 can quickly retrieve breeding data from data center 110, while avoiding data redundancy on the chain.

[0037] This invention provides a blockchain-based breeding data management method that allows various entities to upload breeding data to the blockchain through authorized nodes. This enables multiple institutions to jointly manage the data, registering ownership, authorizing sharing, and verifying quality, thereby achieving data sharing. This invention can manage breeding data from multiple entities, avoiding redundant experiments, improving breeding research efficiency, protecting the commercial secrets of each entity, and allowing each entity to benefit from data sharing through the consortium blockchain.

[0038] Furthermore, this invention provides a blockchain-based breeding data management system, including a data center, a consortium blockchain, and a smart contract module. The data center stores and manages breeding data, including genotype data, phenotypic data, and environmental data, through a distributed file storage system. The consortium blockchain consists of multiple authorized nodes, each with its own scope of permissions, allowing various entities to upload breeding data to the blockchain and enabling multiple institutions to participate in management. The consortium blockchain stores the hash value, ownership certificate, and shared authorization information for each piece of breeding data. The data center and the consortium blockchain are linked through a core data index. The smart contract module is deployed on the consortium blockchain and is used for data ownership registration, sharing authorization, and quality verification of breeding data, thereby achieving data sharing. This blockchain-based breeding data management system can manage breeding data from multiple entities, avoiding redundant experiments, improving breeding research efficiency, protecting the commercial secrets of each entity, and enabling each entity to benefit from data sharing through the consortium blockchain.

[0039] Figure 4 is a flowchart of another blockchain-based breeding data management method provided by an embodiment of the present invention. As shown in Figure 4, the blockchain-based breeding data management method includes: S210, in the data acquisition and preprocessing stage, the acquired breeding data is entered into the data center through an Internet of Things device, and the breeding data is standardized.

[0040] S220. During the data on-chain and storage phase, the hash value of qualified data is calculated and written into the consortium blockchain after consensus verification.

[0041] S230. During the data sharing and usage phase, data ownership registration, sharing authorization, and quality verification are carried out through the smart contract module.

[0042] S240. In the data traceability and supervision stage, the application layer provides full lifecycle data traceability query and real-time monitoring.

[0043] Specifically, during the data traceability and supervision phase, any authorized entity can input a data ID through the application-layer platform to query the complete lifecycle information of the data, enabling full lifecycle data traceability queries, including the data collection entity, on-chain time, ownership change history, usage records, etc. All information originates from the blockchain, ensuring authenticity and reliability. Regulatory authorities can access the records of the regulatory audit contract in real time through the regulatory nodes of the consortium blockchain to monitor data sharing and usage, achieving real-time monitoring. When the contract detects illegal operations (such as unauthorized downloading of confidential data), it automatically triggers an alert, and regulatory personnel can freeze the permissions of the violating node and conduct an investigation. When disputes arise regarding data ownership or usage, both parties can submit transaction records and ownership certificates on the blockchain as evidence. The regulatory authorities will adjudicate based on contract rules and on-chain records, ensuring the fairness and authority of the ruling.

[0044] In some embodiments of the present invention, the data acquisition and preprocessing stage specifically includes: inputting the collected breeding data into the data center through IoT devices and manual input, and performing preliminary filtering through edge computing nodes; performing standardized format conversion on the breeding data in the data center, and supplementing metadata to generate a temporary ID; triggering a data quality smart contract to automatically detect and score the breeding data according to preset indicators, and only allowing qualified breeding data to enter the next stage.

[0045] This invention provides a blockchain-based breeding data management method, centered on full lifecycle data management. It encompasses four core stages: data collection and preprocessing, data upload and storage, data sharing and use, and data traceability and supervision. Each stage is seamlessly integrated through smart contracts and blockchain technology, ensuring efficiency and reliability. This method manages breeding data from multiple entities, avoiding redundant experiments and improving breeding research efficiency. It safeguards the commercial secrets of each entity and allows them to benefit from data sharing through the consortium blockchain. This achieves reliable full lifecycle management of breeding data from collection, storage, sharing to application, providing a solid data infrastructure for intelligent breeding.

[0046] In this embodiment of the invention, the consortium blockchain 110 includes a main chain and side chains; the main chain is used to manage the ownership of breeding data and the node identity of authorized nodes; the side chains are used to classify breeding data into genotype side chains, phenotype side chains and environmental side chains according to the data type, and each side chain interacts with the main chain through a cross-chain communication protocol.

[0047] The blockchain-based breeding data management method in this embodiment of the invention further includes, during the data uploading and storage stage, managing the ownership of breeding data and the node identity of authorized nodes through the main chain.

[0048] Furthermore, to address the low query efficiency caused by storing different types of data on a single chain, this invention proposes a multi-chain collaborative model where the main chain manages ownership and side chains store data. The main chain and side chains achieve data interoperability through a cross-chain communication protocol. The specific architecture is as follows: The main chain is the ownership chain, serving as the core chain of the entire database. It manages the ownership of breeding data and the node identities of authorized nodes. The main chain only stores core ownership information and cross-chain indexes for breeding data, not the actual data content. The core functions of the main chain include: node identity management (maintaining the identity certificates and permission lists of all authorized nodes within the alliance), data ownership registration (recording the initial owner and ownership change history of each piece of breeding data), side chain management (registering and monitoring the operational status of each side chain), and cross-chain transaction verification (verifying the legality of data sharing transactions between side chains). The main chain design follows a "lightweight" principle, improving transaction efficiency by simplifying data content. Its block generation time is controlled within 10 seconds, thus meeting the requirement for real-time on-chain uploading of breeding data.

[0049] Sidechains can be categorized based on the data type of breeding data, including genotypic sidechains, phenotypic sidechains, and environmental sidechains. They can also include computational result sidechains. Each sidechain interacts with the main chain via a cross-chain communication protocol. Each sidechain can focus on storing and trading a specific type of data, achieving "classified management and precise querying." For example, genotypic sidechains store genome sequencing data and molecular marker data; phenotypic sidechains store field observation data and laboratory testing data; environmental sidechains store meteorological data, soil data, and irrigation data; and computational result sidechains store phenotypic prediction results and gene mapping results based on multi-dimensional data. Each sidechain uses a block structure compatible with the main chain, but field weights can be adjusted according to data characteristics. For instance, environmental sidechains can add a "data update frequency" field to accommodate the need for real-time meteorological data updates.

[0050] In some embodiments of the present invention, the cross-chain communication protocol employs hash locking and smart contract verification mechanisms. The scope of permissions for each authorized node is dynamically adjusted based on data contribution and reputation value; the block structure of the sidechain includes a spatiotemporal tag field, which is used to record the spatial coordinates, time period, and environmental number of the breeding experimental field corresponding to the breeding data, and supports data association queries based on spatiotemporal dimensions.

[0051] The blockchain-based breeding data management method in this embodiment of the invention further includes, during the data uploading and storage stage: recording the spatial coordinates, time period and environment number of the breeding test field corresponding to the breeding data through a spatiotemporal tag field, and the spatiotemporal tag field supports data association query based on spatiotemporal dimension.

[0052] Specifically, the cross-chain communication protocol employs a "hash locking + smart contract" mechanism to enable data exchange between the main chain and side chains, as well as between side chains themselves. When a cross-chain data query is required, the initiating node submits a query request to the main chain. After verifying the node's permissions through a smart contract, the main chain generates a temporary hash key and synchronizes it to the target side chain. After verifying the key's validity, the target side chain returns the index and hash value of the corresponding data to the main chain. The initiating node then retrieves the original breeding data from data center 110 using the index. This cross-chain communication protocol mechanism ensures the security of cross-chain data while avoiding data redundancy issues in traditional cross-chain solutions, keeping cross-chain transaction latency within 500 milliseconds.

[0053] In some embodiments of the present invention, the smart contract module 130 includes: a data ownership contract for registering the creator information of breeding data and generating an ownership certificate; a data sharing contract for automatically verifying user permissions and executing point incentive settlement; a data quality contract for scoring the quality of uploaded breeding data; and a regulatory audit contract for recording operation logs of breeding data and detecting violations.

[0054] The blockchain-based breeding data management method in this invention embodiment further includes the following steps in the data sharing and usage phase: registering the creator information of the breeding data and generating an ownership certificate through a data ownership contract; automatically verifying user permissions and executing point-based incentive settlement through a data sharing contract; scoring the uploaded breeding data for quality through a data quality contract; and recording the operation log of the breeding data and detecting violations through a regulatory audit contract. Specifically, the data ownership contract is used to clarify the ownership and change rules of the breeding data. Its core functions include initial registration of data ownership (recording information such as data creator information and creation time, and generating an ownership certificate), ownership transfer (automatically updating ownership information and recording transaction history when data is sold or licensed), and ownership tracing (supporting querying complete ownership change records through data ID). The data ownership contract adopts an "event-driven" mechanism, automatically triggering ownership registration when data is uploaded to the blockchain to ensure the real-time nature of ownership information.

[0055] Data sharing contracts can address the core pain point of "difficult data sharing" by enabling automated authorization and incentives for data sharing. Data sharing contracts can predefine sharing rules for different types of data (such as sharing scope, usage period, and pricing standards). When a user requests data access, the contract automatically verifies the applicant's permissions and account balance. Upon approval, it automatically generates an authorization certificate and deducts the corresponding fee (or data points). Simultaneously, the usage record is written to the blockchain to automatically verify user permissions and execute point-based incentive settlement. For example, if a research institution requests to use a company's corn genotype data, the contract, after verifying sufficient account points, automatically grants 30 days of read-only access and transfers the points to the company's account. The entire process requires no manual intervention, and all records are tamper-proof.

[0056] The data quality contract is used to score the quality of uploaded breeding data, thereby ensuring the reliability of the data uploaded to the blockchain. The data quality contract uses preset data quality evaluation indicators (such as accuracy, completeness, and consistency) to automatically detect the uploaded breeding data. Once breeding data is uploaded to Data Center 110, the contract automatically calls the data quality detection algorithm to score the data. Only data with a score of 80 or above can be uploaded to the blockchain; data with a score below 60 is rejected and a detection report is returned. Data with scores between 60 and 80 is allowed to be uploaded but marked as "pending verification," requiring manual review by an authoritative node within the consortium blockchain 120 (such as agricultural research institutions) before full sharing access can be granted.

[0057] The regulatory audit contract can record operation logs of breeding data and detect violations to meet the needs of government regulatory departments and achieve real-time monitoring and auditing of the use of breeding data. The regulatory audit contract has preset regulatory rules and automatically records all data queries, downloads, and analyses. Regulatory nodes within the consortium blockchain 120 can access these operation logs in real time through the regulatory audit contract. When unauthorized use is detected (such as unauthorized disclosure of trade secrets), the regulatory audit contract automatically triggers an early warning mechanism, freezes the permissions of the violating node, and sends a notification to the regulatory department.

[0058] This invention provides a blockchain-based breeding data management system. This system is used to implement the blockchain-based breeding data management method of any embodiment of this invention. The blockchain-based breeding data management system includes a data center, a consortium blockchain, and a smart contract module. As shown in Figure 2, the blockchain-based breeding data management system includes a data center 110, a consortium blockchain 120, and a smart contract module 130.

[0059] In some embodiments of the present invention, the blockchain-based breeding data management system includes, in sequence, an underlying protocol layer, an infrastructure layer, a blockchain framework layer, a data layer, a contract layer, a business layer, a functional layer, and an application layer.

[0060] Specifically, the data system architecture of the blockchain-based breeding data management system is the core carrier for realizing the technology. The blockchain-based breeding data management system constructed in this embodiment of the invention includes an eight-layer architecture: application layer, functional layer, business layer, contract layer, data layer, blockchain framework layer, infrastructure layer, and underlying protocol layer. It forms a complete technical system with underlying support, middle core, and upper application. Each layer is independent yet closely coordinated to ensure the stability, security, and scalability of the database.

[0061] The underlying protocol layer is used to define the communication and security protocols between the data center 110 and the consortium blockchain 120; the infrastructure layer consists of the hardware devices for the data center 110, the consortium blockchain 120, and the smart contract module 130.

[0062] Specifically, the underlying protocol layer and infrastructure layer are the fundamental guarantees for the operation of the blockchain-based breeding data management system. They provide network communication, hardware support, and security protection for the upper-layer architecture, serving as the "cornerstone" for the stable operation of the entire system. The underlying protocol layer can define the communication and security protocols for each data center. These protocols can include network communication protocols, data transmission protocols, and security encryption protocols. The network communication protocol adopts a hybrid mode of "TCP / IP + blockchain P2P protocol." The TCP / IP protocol is used for regular communication between the data center and the consortium blockchain nodes, while the blockchain P2P protocol is used for distributed data synchronization between nodes, ensuring efficient transmission of breeding data in the distributed network. The data transmission protocol uses the HTTP / 2 protocol, supporting multiplexing and header compression to improve the transmission efficiency of large-capacity breeding data. The security encryption protocol adopts a dual encryption mechanism of "asymmetric encryption + symmetric encryption." Asymmetric encryption (RSA-2048 algorithm) is used for node authentication and digital signatures, while symmetric encryption (AES-256 algorithm) is used for encryption of the original breeding data transmission, ensuring that the breeding data is not stolen or tampered with during transmission. In addition, the underlying protocol layer defines a data standard protocol to ensure that breeding data can be exchanged without obstacles between different authorized entities.

[0063] The infrastructure layer, serving as the hardware for Data Center 110, Consortium Blockchain 120, and Smart Contract Module 130, comprises hardware and basic software, including computing devices, storage devices, network devices, and fundamental support software. The computing devices employ a hybrid "edge computing + cloud computing" model. Edge computing nodes are deployed near breeding experimental fields and laboratories to collect phenotypic and environmental data in real time and perform preliminary processing, reducing data transmission pressure. Cloud computing nodes utilize a distributed server cluster deployed in Data Center 110, providing powerful computing capabilities for big data analysis and smart contract execution. Storage devices combine "distributed storage + local storage." Distributed storage systems (such as Ceph) are used to store shared breeding data, while local storage is used for storing core business confidential data, balancing sharing needs with privacy protection. Network devices include high-performance routers, switches, and firewalls, constructing an "internal and external network isolation" network architecture. The internal network is used for communication between authorized nodes of Consortium Blockchain 120, while the external network only opens limited application interfaces to prevent external network attacks. The basic supporting software includes an operating system (Linux server version), a database management system (MySQL + MongoDB, used for structured and unstructured data management respectively) and virtualization software (VMware), providing a stable operating environment for upper-layer software.

[0064] Both the blockchain framework layer and the data layer are located in data center 110. The blockchain framework layer is used to manage breeding data, while the data layer is used to store breeding data through a distributed file storage system.

[0065] Specifically, the blockchain framework layer and data layer are the core technological carriers of the breeding data management system, enabling the implementation of blockchain functions and efficient storage of breeding data. This is the core source of the trustworthiness of the blockchain-based breeding data management system. The blockchain framework layer manages breeding data and is based on the open-source consortium blockchain framework Hyperledger Fabric, whose modular design and controllable permissions perfectly suit the needs of this research. Through customized development of the framework, the following core functions are implemented: a node management module (maintaining the identity registration, permission allocation, and status monitoring of authorized nodes in the consortium blockchain 120), a consensus mechanism module (integrating a PBFT+PoS hybrid consensus mechanism, supporting dynamic adjustment of consensus parameters), a smart contract engine (supporting both Solidity and Go programming languages ​​to meet contract development needs in different scenarios), and a block management module (responsible for block generation, verification, and storage, achieving collaborative management between the main chain and side chains). Furthermore, the blockchain framework layer also developed a cross-chain interaction module to achieve data interoperability with other agricultural-related blockchain platforms, expanding the application scope of the breeding data management system.

[0066] The data layer enables "hierarchical storage" and "efficient management" of breeding data. It stores breeding data through a distributed file storage system and comprises both on-chain and off-chain data storage. On-chain data is stored in the authorized nodes of the consortium blockchain (120 nodes) and primarily includes block data (block headers, core data indexes, etc.), transaction data (ownership changes, sharing authorizations, etc.), and smart contract code. It uses LevelDB, a database with high-performance key-value pair queries, to meet the rapid retrieval needs of blockchain data. Off-chain data is stored in a distributed data center and includes raw breeding data (genome sequences, phenotypic images, meteorological data, etc.) and preprocessed data results. It employs a hybrid "structured + unstructured" storage model. Structured data (such as plant height, yield, and other numerical data) is stored in a MySQL database, while unstructured data (such as gene sequence files, phenotypic images, etc.) is stored in MongoDB and a distributed file system. The data layer also implements a "data index mapping" function, which accurately links on-chain data with off-chain data through the core data index, ensuring that users can quickly locate the original off-chain breeding data when querying on-chain data.

[0067] The contract layer, business layer, and functional layer are the "central nervous system" of the breeding data management system. The automated execution of data sharing, the process management of breeding business, and the modular implementation of core functions directly determine the application value of the database.

[0068] The contract layer is the core of blockchain technology implementation. By setting up data ownership contracts, data sharing contracts, data quality contracts, and regulatory audit contracts in the smart contract module 130, the automation, trustworthiness, and transparency of breeding data management can be achieved.

[0069] The contract layer is specifically used in smart contract module 130 to set up data ownership contracts, data sharing contracts, data quality contracts, and regulatory audit contracts. These four core categories of smart contracts cover the entire lifecycle management of data.

[0070] The business layer includes a germplasm resource management module, a breeding experiment management module, a data sharing management module, and a variety approval management module. The germplasm resource management module is used for the storage, preservation, propagation, updating, and release of germplasm resources for various crops. The breeding experiment management module is used to connect to edge computing devices, collect field data in real time, and associate genotype and environmental data in the breeding data to generate experiment reports. The data sharing management module provides a convenient entry point for data sharing and acquisition. The variety approval management module completes the approval process for breeding data.

[0071] Specifically, the germplasm resource management module can realize the full life cycle management of germplasm resources of various crops, including germplasm resource entry (recording resource name, source, genotype information, etc., and generating a unique resource ID), preservation management (recording storage conditions, preservation period, etc., and automatically reminding resource updates), propagation update (recording phenotypic data during the propagation process and linking genotype and environmental data), and exit management (recording resource requisition information and realizing requisition authorization through smart contracts). The germplasm resource management module is deeply integrated with the data ownership contract to ensure that the ownership of germplasm resources is clear and traceable. The breeding experiment management module interfaces with edge computing devices to collect field data in real time and correlate it with genotype and environmental data in the breeding data. The module covers the entire process from hybrid combination design to variety selection, including experiment design (recording hybrid combination schemes, experimental field allocation, and other information), data acquisition (interfacing with edge computing devices to collect field phenotypic and environmental data in real time), data analysis (calling the data center's computing engine to perform phenotypic prediction and gene localization), and result evaluation (generating experiment reports based on multi-dimensional data to provide a basis for variety selection). The breeding experiment management module collaborates with data quality contracts to ensure the reliability of experiment data, and records the experiment process through blockchain to ensure the reproducibility of experiment results.

[0072] The data sharing management module provides users with a convenient entry point for data sharing and acquisition. Users can publish shared data (set sharing rules and incentive standards), query shared data (quickly locate the required data through multi-dimensional filtering conditions), and apply for usage permissions (automatically triggering the data sharing contract for permission verification) through the data sharing management module. The data sharing management module also provides a data points management function, allowing users to query their points balance, points acquisition and usage records, and incentivize data sharing behavior.

[0073] The variety approval management module can meet the needs of government variety approval departments, digitize the variety approval process, and complete the approval process for breeding data. The approval process for breeding data includes approval application (enterprises submit variety information, experimental data, and other materials, which are automatically uploaded to the blockchain for evidence storage), material review (approval agencies retrieve materials through the blockchain for online review), on-site inspection (the inspection results are recorded and uploaded to the blockchain to ensure the credibility of the inspection process), and public announcement of approval results (the approval results are written into the blockchain and made public). The variety approval management module uses the immutability of the blockchain to prevent fraudulent behavior in the variety approval process and improve approval efficiency.

[0074] The functional layer provides modular core functional support for the business layer, enabling "functional reuse and flexible expansion," including five core functional modules: data acquisition, data processing, data query, access control, and security protection.

[0075] The data acquisition module supports automated acquisition of multi-source data, including IoT acquisition (connecting to sensors, drones, phenotyping instruments, etc., to collect environmental and phenotypic data in real time), laboratory acquisition (connecting to gene sequencers, protein analyzers, etc., to collect genotype data), and manual data entry (providing a standardized entry interface to supplement manually observed data). The data acquisition module supports automatic data format conversion to ensure that breeding data from different sources can meet data standardization requirements.

[0076] The data processing module can integrate data cleaning, standardization, fusion, and analysis functions. The data cleaning and standardization functions are connected with the data preprocessing process described above. The data fusion function associates and merges genotype, phenotype, and environmental data through spatiotemporal tags to generate a complete data chain. The data analysis function provides basic statistical analysis and visualization tools, and also supports integration with third-party analysis software (such as R and Python) to meet the personalized analysis needs of breeders.

[0077] The data query module provides multi-dimensional and efficient query functions, supporting queries based on multiple conditions such as data type, time and space conditions, ownership subject, and data source. It adopts "index caching + distributed query" technology to cache frequently used query results in memory, improving query response speed. Complex query requests are split into multiple nodes for parallel processing through the distributed query engine, and the query latency is controlled within 1 second.

[0078] The access control module, based on a role-permission model, enables fine-grained access control. Users are categorized into different roles such as breeders, enterprise administrators, researchers, and regulators, with each role assigned a clearly defined scope of permissions (e.g., regulators can query all data operation records but have no data modification permissions). The access control module works in conjunction with data ownership contracts, automatically updating permission configurations when data ownership changes, ensuring dynamic accuracy of permissions.

[0079] The security protection module can build a multi-layered protection system, including node security (authorized nodes must pass identity authentication and qualification verification to access), data security (encryption throughout the entire process of data transmission, storage, and use), transaction security (smart contracts automatically verify the legality of transactions to prevent malicious transactions), and terminal security (security detection of terminal devices accessing the system to prevent malicious terminals from accessing). The security protection module also provides a security log function to record all security events and support post-event traceability and analysis.

[0080] The application layer serves as the "window" for interaction between the breeding data management system and users. It meets the needs of different users through diverse application formats, ultimately realizing the technological value. In some embodiments of this invention, the application layer provides three application formats: a web platform, a mobile app, and an API interface. It also connects with third-party systems through RESTful interfaces, covering various usage scenarios.

[0081] The web-based platform targets core applications from seed companies, research institutions, and regulatory authorities, providing comprehensive functional services, including data management (uploading, querying, and sharing breeding data), business processing (germplasm resource registration, variety approval applications, etc.), data analysis (data visualization, statistical analysis), and system management (permission configuration, security settings). The web-based platform adopts a responsive design, supports access from terminal devices of different sizes, and its interface design follows the principle of "simplicity and ease of use," optimizing the operation process for breeders' usage habits and reducing the learning curve.

[0082] The mobile app is primarily aimed at field breeders and grassroots agricultural technicians, focusing on providing data collection and query functions. Breeders can use the app to capture phenotypic images in real time and input field observation data; the app automatically associates spatiotemporal tags and uploads the data to the data center. Agricultural technicians can use the app to query the genotype and phenotypic information of the main varieties promoted in their area, providing planting guidance to farmers. The mobile app supports offline mode, storing data in environments without network access, and automatically synchronizing to the platform once the network is restored, meeting the needs of field operations.

[0083] The API interface provides third-party organizations with data integration and function call interfaces, supporting integration with the internal breeding systems of seed companies, the analysis platforms of research institutions, and the regulatory systems of government departments. The interface adopts a RESTful style, providing standardized call documentation and testing tools, and supports custom data format configuration to meet the personalized needs of different organizations. Through the API interface, the functions and data resources of the breeding data management system can be "openly shared," building an ecosystem for intelligent breeding.

[0084] This invention also provides a workflow for a blockchain-based breeding data management system. The overall workflow centers on full lifecycle data management, encompassing four core stages: data acquisition and preprocessing, data upload and storage, data sharing and use, and data traceability and supervision. Each stage is seamlessly integrated through smart contracts and blockchain technology, ensuring the efficiency and reliability of the process. Figure 5 is a flowchart of the blockchain-based breeding data management system provided in this invention. As shown in Figure 5, the workflow of the blockchain-based breeding data management system includes: S1, data acquisition and preprocessing.

[0085] The data acquisition and preprocessing steps serve as an off-chain preparation phase. The core objective of data acquisition and preprocessing is to obtain high-quality breeding data, laying the foundation for subsequent on-chain processing and applications. This process is primarily completed collaboratively by the authorized entities (enterprises, research institutions) to be data acquired and the data center 110. The process steps are as follows: 1. Multi-source data acquisition: Breeding enterprises and research institutions collect environmental and phenotypic data through IoT devices (sensors, drones, etc.), collect genotypic data through laboratory equipment, and manually supplement and enter data such as experimental design and field management. The breeding data undergoes preliminary filtering through edge computing nodes to remove obvious noise data before being transmitted to the data center 110.

[0086] 2. Data standardization processing: Data center 110 calls the data processing module to convert the format of the collected breeding data to conform to the standardized format of the database; at the same time, it supplements the data element information (source, collection device, time, etc.) and assigns a unique temporary ID to the data.

[0087] 3. Data Quality Inspection: Data Center 110 triggers the data quality contract, which automatically inspects the data according to preset indicators and generates a data quality score and inspection report. For unqualified data, it is returned to the authorized entity for correction, while qualified data enters the next stage.

[0088] S2, Data Uplink and Storage.

[0089] Step S2 achieves trusted data storage, ensuring clear data ownership and immutability through blockchain technology. The core is completed collaboratively by the authorized nodes of Data Center 110 and Consortium Chain 120: 1. Data hash calculation: Data Center 110 uses a "double hash" mechanism to calculate the data fingerprint of qualified data, and at the same time generates a core data index (including data ID, type, storage location and other information).

[0090] 2. Ownership Registration and Transaction Generation: The authorized entity that collects data submits a data on-chain application through the business layer, triggering a data ownership contract. The contract records the data ownership information and generates an ownership certificate. Data Center 110 can package the core data index, data fingerprint, and ownership information into a transaction request and send it to the authorized node of Consortium Chain 120.

[0091] 3. Consensus Verification and Block Generation: After receiving a transaction request, the authorized nodes of the consortium blockchain 120 verify the transaction through a hybrid consensus mechanism of "PBFT+PoS". After the verification is successful, the block management module writes the transaction data into a new block. The block is associated with the previous block through a chain structure and is simultaneously synchronized to all authorized nodes within the consortium blockchain 120.

[0092] 4. Tiered storage: Core data index and transaction data are stored in the authorized nodes of the consortium blockchain 120. The original breeding data is classified and stored in the distributed storage system of data center 110 (shared data) or enterprise local storage (confidential data) according to the "shared attributes". Data center 110 realizes the association between on-chain and off-chain data through index mapping.

[0093] S3, Data Sharing and Use.

[0094] The data sharing and usage phase is the core link in realizing data value. The smart contract module 130 automates and trusts data sharing, involving data owners, users, consortium blockchain nodes, and data centers: 1. Data publishing and querying: Breeding data owners publish shared data through the application layer platform, set sharing rules (permission level, usage fee, duration, etc.), trigger the data sharing contract, and the contract writes the shared information into the blockchain; users use the query module of the application layer platform to filter data according to their needs, and the platform quickly locates the target data through on-chain indexes.

[0095] 2. Permission Application and Verification: Users submit a data usage application, specifying the purpose of use and permission requirements; the data sharing contract automatically verifies the user's identity, account points (or balance) and data sharing rules, and generates an authorization certificate upon approval, which is synchronized to the user and data center 110.

[0096] 3. Data Acquisition and Use: Users can access the original breeding data through Data Center 110 with their authorization credentials. Data Center 110 records the usage log and synchronizes it to the blockchain. Users can use the data within the authorized scope (such as for analysis and research). If they need to exceed the authorized scope (such as for secondary sharing), they need to resubmit an application and pass the contract verification.

[0097] 4. Incentives and Settlement: The data sharing contract automatically transfers the fees (or points) paid by users to the data owner's account according to preset rules and records the transaction details; the data owner's points can be used to redeem other data or platform services, forming an incentive loop for data sharing.

[0098] S4. Data traceability and supervision.

[0099] The data traceability and supervision phase spans the entire data lifecycle. Through the traceability characteristics of blockchain and regulatory contracts, it ensures that data use is compliant and ownership is clear. It involves regulatory authorities, authorized nodes of the consortium blockchain 120, and data center 110, including: 1. Data traceability query: Any authorized entity can enter the data ID through the application layer platform to query the complete lifecycle information of the data, including the collection entity, the time of on-chain entry, the history of ownership changes, usage records, etc. All information comes from the blockchain to ensure authenticity and credibility.

[0100] 2. Real-time monitoring: Regulatory authorities can access the records of the regulatory audit contract in real time through the regulatory nodes of the consortium blockchain 120 to monitor data sharing and usage. When the contract detects illegal operations (such as unauthorized downloading of confidential data), it will automatically trigger an alert, and regulatory personnel can freeze the permissions of the illegal node and conduct an investigation.

[0101] 3. Dispute Resolution: When disputes arise regarding data ownership or use, both parties can submit transaction records and ownership certificates on the blockchain as evidence. Regulatory authorities will make a ruling based on contract rules and on-chain records to ensure the fairness and authority of the ruling.

[0102] Furthermore, the traditional blockchain block structure mainly consists of a block header and a transaction list. This invention's blockchain-based breeding data management system, combined with the characteristics of breeding data, customizes and optimizes the block structure, designing a four-part structure: "block header + core data index + transaction certificate + spatiotemporal tag." The functions and field definitions of each part are as follows: Block header: Retains the core trusted fields of the blockchain, including version number (identifying the data model version and supporting subsequent upgrades), previous block hash value (realizing the chain-like association between blocks and ensuring immutability), Merkle root (verifying the integrity of data within the block), timestamp (recording the time data is uploaded to the chain, accurate to milliseconds), difficulty value (used for adjusting the computing power of the consensus mechanism), and random number (a core parameter of the consensus mechanism). The Merkle root field specifically introduces a "multi-dimensional hash calculation" method, calculating the hashes of different types of data (genotype, phenotype, and environmental type) within the block separately, and then summing them to calculate the root hash. This ensures data integrity while supporting rapid verification of single-type data.

[0103] Core Data Index: Serving as a crucial link between the consortium blockchain and the data center, this section does not store the original data. Instead, it stores unique index information of the original data within the data center, including the data ID (using UUID format to ensure global uniqueness), data type (labeled as genotype / phenotype / environmental type / calculation result, etc.), data size (facilitating rapid data location within the data center), and storage node address (recording the storage location of the original data in the distributed data center). Through the core data index, consortium blockchain nodes can quickly retrieve the original data from the data center while avoiding data redundancy on the blockchain.

[0104] Transaction Certificate: Records ownership changes and sharing authorization information for breeding data. Core fields include the data owner's public key (identifying the data owner), the authorized recipient's public key (clarifying the scope of data sharing), authorization permissions (divided into different levels such as "read-only," "query," and "secondary analysis"), transaction time (accurate to milliseconds), and digital signature (the data owner's encrypted signature to ensure the legality of the authorization). This data is the core basis for smart contract execution. For example, when an authorized recipient requests to use data, the smart contract automatically verifies the permission information in the transaction certificate, and only allows access to the data index after verification.

[0105] Spatiotemporal tags: Designed to address the spatiotemporal correlation of breeding data, core fields include spatial coordinates (recording the latitude and longitude of the breeding test field, plot number, etc.), time period (recording the corresponding growth stage of the data, such as sowing period, jointing period, grain filling period, etc.), and environmental number (associating with the corresponding meteorological station and soil monitoring equipment number). The introduction of spatiotemporal tags enables data from different dimensions to be quickly correlated based on the "spatiotemporal" dimension. For example, breeders can quickly query phenotypic data of different genotypes under the spatiotemporal condition of "a certain plot + a certain year's grain filling period," providing efficient data support for gene-environment interaction analysis.

[0106] It should be noted that the blockchain-based breeding data management system in this embodiment of the invention is not limited to the above modules. Relevant functional modules can be added according to the adaptability of the blockchain-based breeding data management method to achieve the same function and technical effect as the blockchain-based breeding data management method. These will not be elaborated here.

[0107] This invention provides a blockchain-based breeding data management system. This system can manage breeding data from multiple entities, avoiding redundant experiments, improving breeding research efficiency, protecting the commercial secrets of each entity, and enabling data sharing benefits through a consortium blockchain. Furthermore, the blockchain-based breeding data management system adopts a hybrid architecture of "data center + consortium blockchain." By constructing a blockchain chain data model adapted to the characteristics of breeding data, building an eight-layer overall architecture covering the entire business process, and defining standardized workflows, it achieves trusted management of breeding data throughout its entire lifecycle, from collection, storage, sharing to application, providing a solid data infrastructure support for intelligent breeding.

[0108] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A blockchain-based breeding data management method, characterized in that, The blockchain-based breeding data management method includes: in the data acquisition and preprocessing stage, breeding data is input into the data center via IoT devices, and the breeding data is standardized; in the data on-chain and storage stage, hash values ​​are calculated for qualified data, and the data is written into the consortium blockchain after consensus verification; in the data sharing and usage stage, data ownership registration, sharing authorization, and quality verification are performed through a smart contract module; wherein, the data center is used to store and manage the breeding data through a distributed file storage system, and the breeding data includes genotype data, phenotypic data, and environmental data; the consortium blockchain consists of multiple authorized nodes, each with a corresponding scope of permissions; the consortium blockchain is used to store the hash value, ownership certificate, and sharing authorization information of each piece of breeding data; the data center and the consortium blockchain are associated with the breeding data through a core data index; the smart contract module is deployed on the consortium blockchain and is used to register data ownership, authorize sharing, and verify the quality of the breeding data.

2. The blockchain-based breeding data management method according to claim 1, characterized in that, Also includes: During the data traceability and supervision phase, the application layer provides full lifecycle data traceability query and real-time monitoring.

3. The blockchain-based breeding data management method according to claim 1, characterized in that, The data acquisition and preprocessing stage specifically includes: inputting the collected breeding data into the data center via IoT devices and manual input, and performing preliminary filtering by edge computing nodes; performing standardized format conversion on the breeding data in the data center and supplementing metadata to generate a temporary ID; triggering a data quality smart contract to automatically detect and score the breeding data according to preset indicators, and allowing only qualified breeding data to enter the next stage.

4. The blockchain-based breeding data management method according to claim 1, characterized in that, The consortium blockchain includes a main chain and side chains; the side chains are divided into genotype side chains, phenotype side chains, and environment-type side chains, and each side chain interacts with the main chain through a cross-chain communication protocol; The data uploading and storage phase also includes: managing the ownership of the breeding data and the node identity of the authorized nodes through the main chain.

5. The blockchain-based breeding data management method according to claim 4, characterized in that, The cross-chain communication protocol employs hash locking and smart contract verification mechanisms; the scope of permissions for each authorized node is dynamically adjusted based on data contribution and reputation value. The block structure of the sidechain includes a spatiotemporal tag field. During the data uplink and storage phase, the method further includes: recording the spatial coordinates, time period, and environmental number of the breeding experimental field corresponding to the breeding data through the spatiotemporal tag field. The spatiotemporal tag field supports data association queries based on spatiotemporal dimensions.

6. The blockchain-based breeding data management method according to claim 4, characterized in that, The smart contract module includes: a data ownership contract for registering the creator information of the breeding data and generating an ownership certificate; a data sharing contract for automatically verifying user permissions and executing point-based incentive settlement; a data quality contract for scoring the quality of the uploaded breeding data; and a regulatory audit contract for recording the operation logs of the breeding data and detecting violations. During the data sharing and usage phase, the module further includes: registering the creator information of the breeding data and generating an ownership certificate through the data ownership contract; automatically verifying user permissions and executing point-based incentive settlement through the data sharing contract; scoring the quality of the uploaded breeding data through the data quality contract; and recording the operation logs of the breeding data and detecting violations through the regulatory audit contract.

7. A blockchain-based breeding data management system, characterized in that, The blockchain-based breeding data management system is used to implement the blockchain-based breeding data management method according to any one of claims 1-6. The blockchain-based breeding data management system includes a data center, a consortium blockchain, and a smart contract module.

8. The blockchain-based breeding data management system according to claim 7, characterized in that, The blockchain-based breeding data management system further includes, in sequence, a bottom protocol layer, an infrastructure layer, a blockchain framework layer, a data layer, a contract layer, a business layer, a functional layer, and an application layer. The bottom protocol layer defines the communication and security protocols between the data center and the consortium blockchain. The infrastructure layer comprises the hardware devices of the data center, the consortium blockchain, and the smart contract module. Both the blockchain framework layer and the data layer are located in the data center. The blockchain framework layer manages the breeding data. The data layer stores the breeding data using a distributed file storage system. The contract layer sets up data ownership contracts, data sharing contracts, data quality contracts, and regulatory audit contracts within the smart contract module.

9. The blockchain-based breeding data management system according to claim 8, characterized in that, The business layer includes a germplasm resource management module, a breeding experiment management module, a data sharing management module, and a variety approval management module. The germplasm resource management module is used for the storage, preservation, propagation, updating, and release of germplasm resources for various crops. The breeding experiment management module is used to connect to edge computing devices, collect field data in real time, and associate the genotype data and environmental data in the breeding data to generate experiment reports. The data sharing management module provides a convenient entry point for data sharing and acquisition; the variety approval management module completes the approval process for the breeding data.

10. The blockchain-based breeding data management system according to claim 9, characterized in that, The application layer provides three application forms: web platform, mobile APP and API interface, and connects with third-party systems through RESTful interface.

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