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In light of lack of quantitative analysis in the traceability process of pelagic fishing and the limited credibility of the analysis results, the traceability process of pelagic fishing was examined in detail by using salmon as an example. A freshness index evaluation system for pelagic fishing products was established based on the analytic hierarchy process. By applying this method to the evaluation of freshness, a standardized and replicable process for assessing the quality of pelagic fishing products was created, a freshness scoring formula was proposed and standardized product freshness evaluation was achieved. By incorporating ECDSA signature technology and smart contracts, accurate identification of traceability responsibility was achieved. Furthermore, by introducing credit score data, a two-way enterprise reputation evaluation model with reward, punishment, and compensation mechanisms was established to ensure both enthusiasm from credit evaluation subjects and authenticity of freshness score data. This approach enabled trusted traceability of product freshness. The security of this credit evaluation model was of paramount importance, which was addressed by ensuring that the system was as secure as the underlying ECDSA private keys, thus confirming the credibility, security, and immutability characteristics of the credit evaluation model. Performance test results indicated that read and write throughput for traceability data remained above 500TPS and 150TPS, respectively;reading success rate reached 100% while writing success rate standed at 98%. The average time for data writing was 0.416 s while data querying tooks an average time of 0.142 s. Compared with blockchain-based agricultural products trusted traceability models relying on reliable enterprise reputation evaluation mechanisms, storage efficiency was increased by 55.8%, query efficiency was improved by 63.4%, effectively meeting actual product traceability business needs.