Abstract: To address the issues of data tampering, low credibility, and high on-chain storage pressure in aquaculture, this study constructs a blockchain-based data storage and traceability model for aquaculture. The model adopts a hierarchical storage strategy, where unstructured data such as videos and images generated in aquaculture are stored in IPFS, with only their hash addresses recorded on the blockchain. Additionally, encryption techniques are integrated to enhance data security. For structured data collected by sensors, a batched on-chain mechanism is designed, and data compression algorithms are introduced to reduce on-chain storage costs. Meanwhile, smart contracts are employed to enable automatic data verification. Using pufferfish aquaculture data as an example, the model is implemented and tested on a Hyperledger Fabric consortium blockchain. The results demonstrate that the proposed blockchain-based data storage and traceability model effectively ensures reliable traceability of aquaculture data. The value density of on-chain data is improved by approximately 91.6%, the transaction throughput reaches up to 300 TPS, and the average transaction latency is 0.5 seconds. These results indicate that the model significantly alleviates on-chain storage pressure and meets the traceability and storage requirements of aquaculture data.

Key words: Blockchain, Aquaculture, Smart Contract, Data Storage, IPFS

摘要： 针对目前水产养殖过程中生产数据易篡改、可信度低及链上存储压力大等问题，构建了基于区块链技术的水产养殖数据存储与溯源模型。该模型采用分级存储策略，将水产养殖中产生的视频与图像等非结构化数据存储于IPFS，仅将其哈希地址上链，并结合加密技术增强数据安全性。针对传感器采集的结构化数据，设计分批上链机制并引入数据压缩算法以降低链上存储开销，同时通过智能合约实现数据的自动校验。以基于Hyperledger Fabric的河豚养殖联盟链为例进行测试。结果显示：构建的基于区块链的数据存储与溯源模型可实现水产养殖数据的可信溯源，链上数据价值密度提高了约91.6%，交易吞吐量可达300 TPS，交易平均时延为0.5 s，显著缓解了链上存储压力，满足水产养殖数据的溯源与存储需求。 

关键词: 区块链, 水产养殖, 智能合约, 数据存储, IPFS