Data storage and query optimization for Blockchain-based agricultural supply chains using storage light nodes

The agricultural product supply chain comprises numerous links, generates a substantial amount of data, and is susceptible to high data loss rates, posing significant challenges to data management and traceability. While ensuring data integrity, the high redundancy storage of blockchain increases resource consumption and limits the participation of resource-constrained nodes. To address this gap, we propose a Storage Light Node (SLN) model for the characteristics of the agricultural supply chain. This model integrates a cold/hot data classification mechanism based on identity relevance, generation time, and query frequency, and realizes the selective local storage of high-priority data. A query optimization strategy based on Bloom filters was designed, which accelerated the speed of data retrieval. Experiments using 50,563 real records from the agricultural product supply chain show that compared with the full node, SLN reduces the storage usage by 95.10%, and the average query time is 30.91 ms, which is much faster than the traditional light node. This model provides a scalable and efficient solution for blockchain-based agricultural traceability.