## 5 Fraud Risk Management in the Honey Sector--The VACCP Approach and Innovative Technologies
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Vulnerability Area** & **Risk Factor** & **Corrective Actions** \\ \hline Economic Attractiveness & High price of Manuka, organic (BIO), and regional honeys & Documentation verification, laboratory analyses, origin certification, traceability systems, market control (e.g., price monitoring) \\ \hline Technical Feasibility of Fraud & Addition of sugar syrups, blending with imported honeys & NMR testing, sugar analysis (HPAEC-PAD, FTIR), pollen analysis (AI), isotopic profiling, detection of adulteration using spectroscopic techniques \\ \hline Insufficient Supply Chain Oversight & Lack of uniform control standards outside the EU, regulatory disparities & Supplier certification (BRCGS, IFS Food), compliance audits, strengthening traceability mechanisms, collaboration with local inspections and certification bodies \\ \hline Complex Supply Chain & Lack of transparency and traceability, large number of intermediaries & Digital traceability systems, batch geolocation, blockchain, electronic supplier records, early warning systems \\ \hline Variable Botanical and Geographical Origin & Diverse pollen sources, difficulty verifying origin & Pollen reference databases, pollen geolocation, chemical and isotopic profiling, DNA analysis, botanical validation \\ \hline Low Operational Awareness & Lack of knowledge about specific risks & Staff training, internal audits, awareness programs, industry-specific checklists, risk indicators \\ \hline Low Data Quality & Incomplete or outdated analytical data & Regular database updates, data flow automation, integration with ERP systems, quality control of input data \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Vulnerability areas in the honey sector and proposed preventive actions within the VACCP system. consistency between declared origin and reference data (e.g., pollen profiles) but also early anomaly detection and fraud identification, supporting early-warning systems [59, 60]. Integrating these tools with traceability platforms and Business Intelligence (BI) systems enables dynamic risk management, early threat detection, and continuous monitoring of supply chain integrity. This is crucial for preventing fraudulent practices in international trade and for maintaining the transparency and credibility of quality assurance systems, ultimately supporting consumer trust in authentic honey products. Development of a Systemic Approach to Honey Authenticity Assessment--Case Study from a Research and Development Project  
Between 2022 and 2024, the first two phases of a research and development project were conducted, with the primary objective of creating a comprehensive, automated system for honey authenticity assessment. This system integrates pollen analysis with artificial intelligence (AI) technologies, creating a solution that addresses both laboratory and operational requirements. The project adopted a process-oriented approach, including data standardization, laboratory automation, IT infrastructure design, and integration with food quality and safety management systems. A critical milestone of the project was the creation of a large-scale database of microscopic pollen images from honey samples representing four major geographical regions: Europe, Asia, Africa, and the Americas. In total, over 100,000 images were collected in accordance with the PN-A-77626 [87] standard and the European standard CELEX-32001L0110-PL-TXT [88], ensuring technical consistency and high reference value [59]. Sample images were captured using in-house equipment as well as obtained from partner organizations. The imaging and sample preparation procedures were developed in accordance with the Polish Standard PN-88/A-77626. According to this standard, after dissolving the honey sample in distilled water, the mixture was centrifuged (3000 RPM, 10 minutes) to separate the pollen sediment from the rest of the solution.