An Agile and Scalable Hybrid Blockchain Architecture for Seed Traceability

Digital transformation and transparency in the seed supply chain are cornerstones of national food security and sustainable agricultural development. Existing agricultural traceability systems suffer from elevated storage overhead and performance degradation with massive seed data processing and fail to iterate quality supervision standards without disrupting continuous business operation. To address these problems, this study proposes a dual-optimization architecture-based traceability system for seed supply chains. An edge-assisted Merkle-tree dimension-reduction aggregation protocol is introduced to compress seed logistics scanning data before blockchain submission. Instead of storing each circulation record as an independent on-chain state update, the proposed scheme anchors one fixed-size Merkle root for each aggregated batch, reducing the per-batch on-chain payload to a constant size and lowering the overall on-chain anchoring burden from record-level growth to batch-level growth. Furthermore, it adopts a decoupled regulatory architecture based on the Strategy Pattern for the separation of traceability state storage and compliance inspection logic, enabling uninterrupted rule switching under the tested upgrade scenario via on-chain hash pointer adjustment. Rigorous statistical evaluation of the experimental results indicates that the system stably processes seed circulation records at a peak effective throughput of 1952.4 transactions per second. Under high-frequency concurrency, the 95th percentile (P95) latency remains controlled under 0.28 s. The average physical on-chain storage for 100,000 circulation records was reduced to 0.52 MB, and deploying a new quality inspection rule takes an average of only 2.2 s, with limited computational resource overhead.

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Publication Details

Journal
Agriculture
Published
2026-05-12
DOI
https://doi.org/10.3390/agriculture16101053
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00

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article

An Agile and Scalable Hybrid Blockchain Architecture for Seed Traceability

J Zhang, Xuyang Liu, Siqi Liu, Zemiao Du et al.
Agriculture
Smart Agriculture and AI
article

An Agile and Scalable Hybrid Blockchain Architecture for Seed Traceability

J Zhang, Xuyang Liu, Siqi Liu, Zemiao Du, Xiaofei Fan
article en

Abstract

Digital transformation and transparency in the seed supply chain are cornerstones of national food security and sustainable agricultural development. Existing agricultural traceability systems suffer from elevated storage overhead and performance degradation with massive seed data processing and fail to iterate quality supervision standards without disrupting continuous business operation. To address these problems, this study proposes a dual-optimization architecture-based traceability system for seed supply chains. An edge-assisted Merkle-tree dimension-reduction aggregation protocol is introduced to compress seed logistics scanning data before blockchain submission. Instead of storing each circulation record as an independent on-chain state update, the proposed scheme anchors one fixed-size Merkle root for each aggregated batch, reducing the per-batch on-chain payload to a constant size and lowering the overall on-chain anchoring burden from record-level growth to batch-level growth. Furthermore, it adopts a decoupled regulatory architecture based on the Strategy Pattern for the separation of traceability state storage and compliance inspection logic, enabling uninterrupted rule switching under the tested upgrade scenario via on-chain hash pointer adjustment. Rigorous statistical evaluation of the experimental results indicates that the system stably processes seed circulation records at a peak effective throughput of 1952.4 transactions per second. Under high-frequency concurrency, the 95th percentile (P95) latency remains controlled under 0.28 s. The average physical on-chain storage for 100,000 circulation records was reduced to 0.52 MB, and deploying a new quality inspection rule takes an average of only 2.2 s, with limited computational resource overhead.

AgricultureVol. 16(10)
Hebei Agricultural University (CN), Hebei University of Technology (CN)
Hebei Provincial Department of Bureau of Science and Technology
Zero hunger
Openalex Percentile: Top 6%
Smart Agriculture and AI
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