Food fraud threats in UK post-harvest seafood supply chains; an assessment of current vulnerabilities

The paper addresses the vulnerability of UK post-harvest seafood supply chains (cod, prawns, salmon) to food fraud amid complex, globalized networks and recent disruptions (EU exit, COVID-19, war in Ukraine, inflation). Seafood has a documented history of fraud and mislabeling with implications for economy, public health, and marine conservation. The research aims to identify and compare food fraud vulnerabilities across commodities, supply chain nodes (processing, wholesale, retail, food service), business sizes, and certification statuses, and to relate these vulnerabilities to historic fraud incidents. The study emphasizes a situational, structured approach considering opportunities, motivations, and controls, aligning with GFSI’s definition of vulnerability and criminological routine activity theory. It fills a gap as in-depth seafood-focused, UK-based vulnerability assessments had not previously been conducted.

The study situates itself within a growing body of work on food fraud prevention and vulnerability assessment (FFVA). It reviews available tools such as SSAFE FFVA, Food Fraud Advisor’s tool, and EMAlert, originally designed for company-level but adapted for sector/country analyses. Prior assessments have examined spices, Dutch and Chinese milk, extra virgin olive oil, Chinese rice, food service, organic sectors, and cross-chain comparisons. Literature highlights the importance of evaluating fraud drivers (opportunities, motivations) and controls, and combining vulnerability with historical incident data to detect current or emerging threats. Seafood mislabeling is widespread globally, with studies underscoring risks to sustainability and public health. The paper also notes the role of international and national bodies in fraud mitigation and the potential for social desirability bias when firms assess their own practices.

Design: Cross-sectional assessment of food fraud vulnerability using the SSAFE FFVA adapted to seafood supply chains, combined with a review of publicly available fraud incident data. Participants and recruitment: Approximately 500 UK companies across post-harvest nodes (processing, wholesale & distribution, retail, food service) were invited; 32 participated between Jan–Apr 2022. Products covered: cod (n=12), prawns (n=10), salmon (n=10). Company size: small (n=17), medium (n=5), large (n=10). Certification: 17 had third-party accreditation or required it of suppliers. Regions per ONS categories. Consumers were excluded. Instrument: SSAFE FFVA based on routine activity theory, covering opportunities, motivations, and controls with six sub-categories. Two counterfeiting items (Q6, Q7) were omitted as irrelevant; 48 questions remained, preserving original numbering (Q1–5, 8–50). Responses: three levels mapped to scores (opportunities/motivations: 1=low, 2=medium, 3=high; controls reversed). Data collection: Interviews conducted face-to-face, via video, phone, or by email with technical staff or owners. The questionnaire (Excel) was provided in advance for preparation. Ethical approval: Queen’s University Belfast, with written informed consent. Historic fraud data: Open-access sources used to profile 2020 incidents for the three commodities: EU RASFF, HorizonScan, Decernis Food Fraud Database, and Nexis. Analysis: Frequencies of low/medium/high per factor computed; high vulnerability defined as >50% high or >75% medium+high. Multiple correspondence analysis (MCA) performed (XLSTAT) to visualize groupings by commodity, node, business size, certification; loadings examined to interpret patterns. Non-parametric tests (IBM SPSS): Mann–Whitney U and Kruskal–Wallis (p<0.05) assessed differences in factor scores by commodity, node, size, certification. For node comparisons, Q8 and Q27 were omitted if not applicable.

Overall vulnerability: Across all responses, 45% low, 28% medium, 27% high. Highest perceived vulnerability was in technical opportunities; lowest in opportunities in time/space and motivations. Opportunities:

• Technical opportunities (Low 29%, Medium 12%, High 59% as depicted): High vulnerability in availability/technology/knowledge to adulterate or substitute, especially raw materials (low 16%, medium 9%, high 75%) versus final products (low 32%, medium 23%, high 45%). Detection vulnerability high for both raw (66% high) and final products (71% high). Complexity of adulteration lower when buying whole fish/fillets.
• Opportunities in time/space: Lower vulnerability; controlled production lines (low 71%, medium 19%, high 10%); strong supplier/customer insight and trusted relationships (low 88%); perceived low frequency of fraudulent reports in their own chains, contrasting with literature/media. Motivations:
• Highest single vulnerability factor: attributed value of credence attributes (origin/methods) with 78% high (low 19%, medium 3%, high 78%).
• Price differentials due to regulatory differences: 54% high (low 13%, medium 33%, high 54%). Industry competition high (72% reported highly competitive). Despite disruptions, 84% considered their own company profitable; 65% perceived suppliers profitable; 66% reported not imposing financial strain on suppliers. Controls:
• Technical controls generally medium; 38% had comprehensive fraud monitoring systems; 34% had no fraud detection methods. Mass balance established for own company (54%) and suppliers (74%); fraud contingency planning weak: only 33% had plans including fraud; 47% had none for fraud/safety. Guidance gaps: 33% unaware of fraud mitigation guidance; 30% found guidance inadequate; pronounced in small and food service firms.
• Managerial controls mixed: ethical codes in 78% (56% embedded); whistleblowing in 60% but only 47% with independent anonymous channels; 65% had no integrity screening. National policy perceived comprehensive (low vulnerability 59%), but local enforcement weak (59% medium) with low inspection frequency and low-impact sanctions. MCA patterns: Minimal grouping by commodity or node; stronger clustering by business size (small vs medium/large) and certification (non-certified vs certified), driven largely by control-related factors (higher vulnerability left side, lower right). Statistical differences:
• By commodity: Significant differences in Q1 (complexity of adulterating raw materials; prawns higher), Q25 (supplier country corruption; prawns higher due to sourcing from Vietnam/China/India), Q42 (supplier fraud monitoring; salmon higher perceived vulnerability).
• By supply chain node: Differences concentrated in controls: own information systems (Q36), own tracking/tracing (Q37), supplier information systems (Q43), plus industry guidance (Q46) and enforcement (Q48, Q49). Processing/wholesale had more comprehensive systems than retail/food service; retail/food service less aware of guidance. Food service had notable gaps in knowledge of supplier systems (only 38% answered supplier-control questions).
• By business size: No significant differences in technical opportunities, time/space, or economic drivers. Significant in cultural/behavioral: ethical culture across industry (Q28) lower in small firms; supplier-country corruption exposure (Q25) higher in large firms (more international sourcing). Controls significantly more comprehensive in large firms: integrity screening (Q38), code of conduct (Q39), whistleblowing (Q40), supplier contracts (Q41), supplier info systems (Q43), and contingency plans (Q50).
• By certification: Largest impact. 21 factors differed significantly. Certified companies perceived higher vulnerability for availability/knowledge to adulterate raw materials (Q2/3 context), and higher corruption exposure (Q18, Q25) reflecting international scope; non-certified perceived sector economic health lower (Q26) and higher customer criminal offences (Q27). Controls showed significant differences in 86% of control factors, with certified companies having more robust controls. Non-certified firms answered only 50% of supplier-control questions versus 91% for certified. Historic fraud (2020): 240 incidents: prawns 193 (≈80% illegal/unauthorized veterinary residues, mainly imported farmed Asian prawns), cod 26, salmon 21 (weight/species/fishery substitution/adulteration). Reports most frequent in processing (39%) and food service (42%). Overlaying with FFVA suggests elevated risk in uncertified prawn supply chains (small retail/food service), salmon supplier-control weaknesses, and food service nodes with weaker controls. MSC-certified products have reported mislabeling <1% versus ~30% global average, indicating certification may mitigate risks.

Findings indicate medium overall food fraud vulnerability in UK post-harvest seafood chains, with the greatest weaknesses in technical opportunities and gaps in detection and contingency planning. High vulnerability stems from credence-value attributes and regulatory price differentials, while operational opportunities in time/space are better controlled. Control systems—especially technical monitoring, whistleblowing independence, integrity screening, and contingency planning—are uneven and weaker among small firms, retail, and food service. Certification status emerged as the strongest differentiator of vulnerability, predominantly through more robust control systems and better knowledge of supplier controls among certified companies. Business size and supply chain node also influenced controls, with larger firms and processors/wholesalers exhibiting stronger systems than small firms, retailers, and food service operators. Commodity-specific risks include prawns (ease of adulteration; higher supplier-country corruption) and salmon (weaker supplier fraud monitoring), aligning with historic incident patterns where prawns dominate reported fraud and processing/food service show higher incident prevalence. Integrating vulnerability assessments with historical fraud data helps identify current and emerging hotspots: uncertified prawn supply chains in small retail and food service, salmon chains with weaker supplier control oversight, and food service nodes with limited controls. These insights support prioritizing countermeasures such as strengthening supplier assurance, enhancing traceability, and promoting certification or baseline training focused on fraud prevention. The observed perception gaps (e.g., downplaying own-company final-product risks) also highlight the need to address insider-threat awareness and foster a sector-wide ethical culture.

This study provides the first in-depth assessment of UK post-harvest seafood fraud vulnerability across cod, prawn, and salmon, comparing vulnerabilities by commodity, supply chain node, business size, and certification, and contextualizing with historic incident data. Overall vulnerability is medium, driven by technical opportunities and uneven control measures. Certification is the most influential protective factor, associated with substantially stronger controls. Areas warranting closer scrutiny include uncertified prawn supply chains in small retail and food service businesses, salmon supplier-control weaknesses, and the food service node more broadly. Key contributions include: (1) empirical evidence that certification status is a stronger determinant of vulnerability than commodity, node, or size; (2) identification of specific control-system gaps (fraud detection methods, contingency planning, whistleblowing independence, integrity screening); and (3) a framework linking vulnerability profiles to historic fraud patterns to spotlight current and emerging risks. Future work should differentiate among certification types and their protective effects, incorporate more recent post-2022 data to account for ongoing disruptions, and evaluate targeted interventions (e.g., simplified fraud guidance, affordable certification/analytical tools, enhanced traceability requirements) particularly for small and food service businesses.

• Sample size and self-selection: 32 companies participated; firms confident in their practices may have been more likely to participate, potentially biasing results.
• Underreporting of fraud: Publicly available databases likely capture only a subset of actual incidents; prevalence comparisons may be conservative.
• Timing and generalizability: Data collected in 2022 during ongoing supply chain disruptions; applicability may evolve with market conditions.
• Scope of certification: Analysis did not distinguish among categories (e.g., food safety vs sustainability vs ethical) or their differential protections; certification can also create new fraud incentives via price premiums.
• Incomplete applicability of some items by node: Certain questions were omitted for node comparisons (e.g., Q8, Q27), and food service showed lower knowledge of supplier controls, indicating information gaps.