A Risk-Triggered Hybrid Assurance Framework Integrating Digital Traceability, AI-Based Monitoring, and Selective Laboratory Audits for Organic Supply Chains

2026

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DOI 10.28978/nesciences.262019
Data confidence 70 medium
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Abstract

Organic certification operates on a process-based model that verifies production methods rather than the analytical properties of the final product, leaving a persistent verification gap that documentationonly audits cannot close.This paper proposes a governance-aware hybrid assurance architecture that combines digital traceability -permissioned blockchain, IoT sensors, UAV monitoring, and AI analytics -with laboratory audits triggered selectively by anomaly detection rather than imposed universally.The contribution is a specific architectural integration: AI-driven risk scoring is embedded into an organic compliance workflow as the trigger for laboratory verification, positioned as a complement to -not a replacement for -process certification and control-body oversight.The framework is aligned with the EU Digital Product Passport (DPP) initiative, USDA Strengthening Organic Enforcement (SOE) requirements, and EU Regulation 2018/848, and is examined in the deployment context of Central Asia, where organic sectors are growing rapidly but laboratory infrastructure is still maturing.Validated findings reported in the paper are limited to indicators derived from a 42-farm EU deployment cited in prior work (approximate 34% certification cost reduction; transparency-index improvement; high reported compliance accuracy), reproduced here with explicit methodological caveats.Projected outcomes of the proposed hybrid laboratory integration (target compliance accuracy ≈ 99%; certification cost ≈ $5.00/kg; consumer-confidence uplift of 20-30%) are presented as design targets and testable hypotheses requiring controlled validation, not as empirical results.