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.
