## 2 Authenticity Management in Normative Systems and Food Safety Standards
\begin{table}
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**Method/Technique/Tool** & **Advantages** & **Limitations** & **Accreditation and Validation Requirements** \\ \hline Isotopic Analysis (IRMS) & High specificity in detecting plant sugar adulterants & High costs, difficulties in interpreting results for honeys with similar isotopic profiles & Requires accreditation (ISO/IEC 17025) \\ \hline Spectroscopy (FTIR, NIR, UV-Vis) & Enables rapid chemical profiling, automation, low unit costs & Effectiveness depends on the quality of calibration models and reference databases, sensitivity to interferences & Requires accreditation (ISO/IEC 17025) \\ \hline High-Resolution Spectroscopic Techniques (LC-HRMS, NMR) & High precision and sensitivity, capable of detecting a wide range of chemical markers & Lack of standardized validation protocols, high costs, need for extensive reference databases, limited availability in routine laboratories, no clear standards & Requires accreditation (ISO/IEC 17025), lacks clear standards \\ \hline Chromatography (HPLC, GC-MS) & Accurate detection of botanical markers, residues of adulterants, and foreign compounds & Potential masking by honey matrix components, requires sample preparation and expert interpretation, high costs & Requires accreditation (ISO/IEC 17025) \\ \hline DNA Analysis (MDA) & High precision, capable of detecting a wide range of species, botanical and geographical origin identification & Requires clean samples, highly sensitive to contamination, needs well-developed reference databases, susceptible to DNA degradation, lacks standardized protocols & Requires accreditation (ISO/IEC 17025), industry controversies \\ \hline Omics Technologies (Metabolomics, Proteomics, Genomics) & High specificity and sensitivity, allows simultaneous analysis of multiple compound classes & High costs, advanced infrastructure, requires specialized expertise & Requires accreditation and validation (ISO/IEC 17025) \\ \hline Chemometrics + Hybrid Models & Allows integration of multiple data sources (NIR, pollen, isotopes), high predictive accuracy & High computational and competency requirements, needed interlaboratory validation, standardization challenges & Requires accreditation and validation (ISO/IEC 17025) \\ \hline Physicochemical Analysis & Fast, standardized, allows detection of deviations from reference profiles & Does not allow definitive detection of adulteration methods, limited specificity & Typically does not require certification, but validation is recommended \\ \hline System Elements for Authenticity Management & Support the implementation of VACCP/TACCP, based on risk analysis, audits, and continuous improvement & Require organizational maturity, management commitment, and data availability, high implementation costs & Requires certification (e.g., ISO 22000, FSSC 22000, BRCGS) \\ \hline Documentation Analysis (Traceability) & Low cost, easy to implement, fundamental to quality systems & Highly susceptible to fraud without analytical or audit support, requires reliable source data & Not applicable \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._The recent scientific literature highlights that the effectiveness of these methods can be significantly enhanced through complementary application and integration within food quality and safety management systems [5; 27; 53]. Particularly promising is the combination of pollen, spectroscopic, and chemometric analyses with traceability data, integrated within advanced risk assessment systems based on artificial intelligence (AI) and omics techniques (e.g., proteomics, genomics), as well as hybrid models [54]. Such an approach supports dynamic fraud risk assessment, continuous improvements in preventive measures, and alignment with international standards, such as VACCP, BRCGS, IFS Food, FSSC 22000, and ISO/IEC 17025, which often require method accreditation and validation [11].