Food Investigation Notes PDF

Lecture 2 introduction Monday 9 September 2024 10:30 Introduction - setting the scene Learning outcomes - Describe the principles of food fraud, authenticity, and the relationship with food investigation - Identify different types of food fraud - Distinguish food quality, food safet...

Lecture 2 introduction Monday 9 September 2024 10:30 Introduction - setting the scene Learning outcomes - Describe the principles of food fraud, authenticity, and the relationship with food investigation - Identify different types of food fraud - Distinguish food quality, food safety, food defence and the food fraud issues DEF - Authenticity - the quality of being genuine or real DEF - Fraud - dishonestly calculated for advantage Demarcation of fraud - deceiving others on purpose for personal gain Food Fraud, Global Food Safety Initiative DEF - a collective term encompassing the deliberate and intentional substitution, addition, tampering or misrepresentation of food, food, ingredients or food packaging, labelling production Information or false or misleading statements made about a product for economic gain that could impact consumer health Different types of food Fraud - Substitution - Dilution - Unapproved enhancement - Concealment - Mislabelling - Counterfeiting - Grey market/theft/diversion Different types of 100% fakes - Brand squats - Full copies - Refills of original packaging - Non-compliant packaging - Product overruns Adulterations Imitation - Substitution - counterfeiting - Dilution - Unapproved enhancement - Concealment - Mis-labelling Part Fakes - Removal of fractions, ingredients or constituents - Addition of replacements, enhancers, or concealers DEF - Food Quality - refers to the characteristics of food that makes it desirable or acceptable to consumers DEF - Food Safety - involves the prevention of foodborne illnesses or harm caused by the consumption of food that is contaminated, improperly handled or stored DEF - Food defence - refers to the measures taken to protect the food supply from deliberate contamination or sabotage Food Investigation Page 1 contamination or sabotage DEF - Food Fraud - involves the intentional misrepresentation or adulteration of food products for economic gain Food Investigation Page 2 Lecture 3 history incident Sunday 10 November 2024 12:37 Learning outcomes - Demonstrate comprehension the long history of food fraud and developments over time - Acquire and synthesize information from historical evidence through incident analysis - Apply incident and media analysis as a starting point for further food investigation What kinds of Adulteration in Ancient times? - Romans had limited access to sweeteners. Lead acetate for sweetening, from boiling grape juice (must) in lead kettles. For wine or food dishes. Unwittingly but very toxic - Pepper in Roman times. Juniper berries, myrtle berries, mustard seeds were used to extend pepper - Documentation relating to the first century AD describes the falsification of olive oil by a product made from wood, leaves, and berries of trees, and the falsification of wine by a substance made from a variety of plants French Penalties for Violations - 1480 - Fines, Guild expulsion or corporal punishments: - Exposure “before a fine large fire” of a seller of adulterated butter with the butter placed upon his head until it melted. - “Any man who sells watered milk shall have a funnel placed in his throat and the said watered milk poured down until a doctor or a barber declares that the man cannot swallow any more without danger. Examples Mid-19th century - Sugar weighted with sand - Watered-down milk containing chalk and flour - Lead in wine and cider - Iron sulphate in tea - Hallucinogenic chemicals and copper in rum and beer - Many other potentially lethal ingredients in commonly consumed food - In fact, it was hard to find a basic foodstuff in the early nineteenth century that had not been tampered with in some way Industrialisation = explosion of food adulteration FREDRICK ACCUM RAISED THE ALARM ABOUT FOOD FRAUD Fredrick Accum, a German-born chemist in early 19th-century England, was one of the first to raise the alarm about food fraud. In his 1820 work "Treatise on Adulterations of Food and Culinary Poisons", Accum exposed the widespread use of harmful substances, such as lead and arsenic, in food products to enhance appearance or taste, despite their dangerous health effects. His revelations sparked public outrage and called for Food Investigation Page 3 effects. His revelations sparked public outrage and called for stricter food safety regulations, ultimately influencing future laws and standards in food production and safety. Accum’s pioneering work laid the foundation for modern food safety practices and regulation Changes in Time - Food production Foods from simple to composite/complex More high value foods (spices) Distance between farmers and consumer increasing - Food Adulteration Food identify harder to discover in complex foods More high value foods => more gain per kg Transparency in the chain has gone down Information on Food fraud occurrence - No global registration - Surveys/monitoring conducted is often risk-based - No self-reporting by criminals - Fragmented information: many hold a piece of the jigsaw puzzle The future and the future developments How do global developments impact? - Globalisation of the food supply chain - Food insecurity - Consumer interest rising on how their food is produced - More convenience foods? Globalisation of the food supply chain - Driven largely by those that seek access to wider markets and less expensive sources of raw materials - Emerging countries entering the global food supply chain - Transaction points , complexity , transparency fraud risk -> increasing Food Supply is a complex, global system - Many components (conditions) influence fraud risks in food supply - These behave in non-linear ways when they combine Farmer -> Processor -> Distribution -> Retail - Networks organise themselves, creating order without central control - Complex systems have thresholds -> System might be secure under some conditions => Self-stabilisation - When pushed towards a threshold -> Shocks -> amplifying chaos - Once a system collapses, often subject to hysteresis -> new equilibrium state -> new stabilising properties -> hard to return Covid-19 pandemic Food Investigation Page 4  Covid-19 pandemic - Initially effects on imports from China - E.g., 85% of global dehydrated garlic output from China - Netherlands: ~65% of garlic comes from China - In February 2020 25% price increase of garlic imported into NL - Panic buying - More pressure on supply and demand will affect food fraud in the end too Food Investigation Page 5 Lecture 4 - Impact Analysis Sunday 10 November 2024 13:56 Learning Goals - Understand that gain of the offender and impact/loss of victims are two very different aspects - Identify and distinguish between different types of impact to be considered in impact analysis - To conduct a high level impact analysis on an existing food fraud case Levels of impact - Businesses and the wider environment (chains, tiers) - Consumers - Societal Other damage to consider for impact analysis - Confidence losses - Legal proceedings - Sales losses - Recall losses - Third party losses (extra testing) Consumers - Victims - Most consumers would unknowingly and unintentionally purchase counterfeit/adulterated food products due to them being so closely similar to the genuine product -> they cannot distinguish them Damage to consumers - Financially - Nutritionally - Safety - Breach of certain norms and values (e.g. religious choices or choices with regard to production systems or animal welfare) - Losing faith in food production, retail, society, etc Impact on the wider environment - Food fraud affects intellectual property protection of a region or country - It may also hamper innovation by displacing legitimate sales - Mislabelling can potentially affect the brand image of a region, or even a country Losses for all to consider for impact analysis - Social losses - Punishments - Sales losses & over payment - Recall losses - Confidence losses - Third party losses (e.g. extra testing) Example: The melamine case in China The melamine case in China refers to a major food safety scandal in 2008, where melamine, a toxic chemical used in plastics and adhesives, was illegally added to dairy products to falsely increase protein content. The contamination was discovered when thousands of infants in China became ill after consuming milk powder contaminated with melamine, leading to widespread kidney damage and several deaths. The scandal exposed significant gaps in food safety regulations and corporate oversight in China. It resulted in international outrage, product recalls, and stricter food safety laws. The case highlighted the dangers of food fraud and the severe health risks associated with adulterated food products. Food Investigation Page 6 Value of Milk - Not per volume => Frequent dilutions in history - Payment for valuable components: Milk protein, milk fat, milk lactose - Dilution is useless - Artificial inflation of the protein or fat content? - Protein test is historical and actually not measuring protein Determination of Nitrogen - Kjeldahl method - Nitrogen is converted to protein using the factor 6.38 N - Modifying N results in apparent higher protein concentrations -> higher value IMPACT - Social losses: 240,000 infants got ill, 60,000 were hospitalized, six children died - Punishment: The Chinese court imposed death penalties, imprisonment and fines on the offenders - Financial/sales losses - The scandal resulted in the bankruptcy of the Sanlu Group co, Ltd in 2008, leaving a debt of $160 million. - Ten days after disclosure, the sales of the Chinese companies Mengniu and Yili dropped by 80%, and overall sales of the dairy sector in China dropped by 30-40%. Stock prices of companies dropped between 37-60%. Purchase volume of milk decreased to ~20% of normal sales. - Recall costs: Estimated for the Chinese dairy industry= $3 billion, worldwide recall expenses = $18 billion (based on 30 affected brands in more than 60 countries) - Confidence losses: - Chinese dairy products were boycotted by 30 EU countries and confidence in the Chinese dairy industry plummeted. When interviewed in that period, ca. half of the Chinese consumers perceived at least one of the Chinese dairy products (milk (powder), yoghurt, ice cream) as unsafe. - Third party losses – magnitude unknown Food Investigation Page 7 Lecture 5 - FIIN Sunday 10 November 2024 14:13 The Food Industry Intelligence Network Food Fraud is an ongoing challenge - Supply chain disruptions and vulnerability - Food fraud complexity - Difficulty of detection Why would food companies share (sensitive) information - Allows for a more targeted, intelligence-led approach to supply chain assurance via collective data and insights for industry and regulators - Non-competitive environment with a common aim fosters collaboration, shared learnings and best practice What did FIIN set put to a chieve - To help ensure the integrity of food supply chains and protect the interests of the consumer - To address the recommendations from “The Elliott Report” for industry to establish a ‘safe haven’ to collect, collate, analyse and disseminate information and intelligence - To support food industry members to proactively manage supply chain risk by providing targeted intelligence and training resources - To work with governmental bodies to better understand where risks may sit in the UK food industry from food fraud - To help disrupt those activities and in doing so, further enhance the reputation of the (UK) Food Industry How does fiin work? - Subscription based with fees set at affordable level reflecting business size - All members must participate in supplying data quarterly to fiin (authenticity and traceability) - Data anonymised and consolidated by Legal Host (Eversheds) ensuring Legal Privilege for all data submitted - Members have access to dashboards displaying test results, methods and traceability and the ability to compare their own results with the fiin dataset Fiin Technical Steering Group (TSG) Representatives from 17 fiin member companies: - 10 x Manufacturers - 4 x Retailers - 2 x Food Service - 1 x Independent Expert - Chair and Secretariat (Premier Foods) Our data Journey 2015-2024 - 2015 - launch - Sept 2017 - technical steering Group (TSG) established - April 2020 - board member appointed to lead it project - June 2020 - TSG portal subgroup set-up - May 2021 - data submission portal - live - Nov 2021 - Dashboard development and launch - July 2023 - comparison dashboard launch - Nov 2023 - Data WS 1 Food Investigation Page 8  - Nov 2023 - Data WS 1 - June 2024 - Data WS 2 How many tests? - 2021/2022 - £3,322,409 total spend - 11,065 samples tested Collaborative testing - Enables a comprehensive view of authenticity across the supply chain - 2023 project on edible oils, including olive oil, rapeseed oil & sunflower oil – 66 samples were analysed from members and independent outlets - Next project - basmati rice and illegal dyes & spent material in red spices Honey working group - Established 2021 - Formed to address concerns about sugar addition in honey based on testing results - Challenges identified: Uncertainty with modern test methods vs. statutory tests. - Opaque databases and unclear result interpretation criteria. - High exposure to contentious honey producers (e.g., China). - Difficulty in auditing and conducting mass balance exercises at production sites. - Conflicting evidence: lab tests vs. traceability and producer records. - Priorities - Enhance knowledge of honey testing methods among FIIN members. - Strengthen engagement with UK and EU regulators. What has fiin achieved? - It has brought together a broad spectrum of food businesses to work together to help protect consumers interests and strengthen the UK’s defence against food fraud - Online dashboards provide access to >300,000 test results and enable a more strategic and targeted approach to supply chain assurance - Achieved recognition for its leadership in tackling food fraud and protecting the integrity of the supply chain, both in the UK and globally - Established a mature intelligence sharing relationship / agreement with the UK ‘Regulators’ - it has given a voice to the UK Food Industry on matters of authenticity and integrity - Real-time notifications from fiin members and regulators on key issues Future considerations & strategic priorities - Continue to enhance data quality, depth and insights - Extend fiin support and resources to the SME community - Expand coverage of food groups and supply chain nodes - Identify opportunities for collaboration with partner organisations in the food system Food Investigation Page 9 Lecture 6 - Root cause analysis Sunday 10 November 2024 14:36 Learning Goals Understand the Routine Activities Theory concept Describe various opportunities-related factors and explain why and how they affect food fraud occurrence Distinguish between technical opportunities and opportunities in time and place Use the factors to conduct a root cause analysis Different Approaches - Detecting Fraud when it happens - Reactive, may limit impact - Anticipating Fraud before it happens - pro-active, predictive, prevention The Routine Activities Theory (RAT theory) The Routine Activities Theory (RAT) explains food fraud as a crime occurring when three elements converge: a motivated offender, a suitable target, and the absence of a capable guardian Motivated Offender - individuals or organisations seeking to profit from deception. Usually motivated by financial gain. Suitable target - food products themselves. A "capable guardian" is someone or something that can prevent or deter fraudulent activity Developed by criminologists Lawrence E. Cohen and Marcus Felson in 1979 Converging in time and place (Lilly, 2011) Fraud factors - Opportunities - Technical opportunity and opportunity in time and place - Motivations - Economic drivers and culture and behaviour - Controls - technological controls and managerial controls - = Fraud vulnerability Opportunities Technological opportunities - Complexity of adulteration of your raw materials - Availability of technology and knowledge to adulterate - Detectability = general likelihood of detection Complexity of Fraud - Increases as material goes from solid to solid particles to liquid - Increases as single ingredient, primary agricultural product, to several ingredients to many ingredients, complex food Availability of technology and knowledge Spices - Tradition of mixing for the right flavour - Mixing in starch does not require much knowledge Easy in terms of technology and knowledge? - Replacement of real vanilla with synthetic aromas by spice trader - Matching the isotope ratios of the vanilla molecule Food Investigation Page 10 Detectability - ability to hide deception Suitable target (opportunities) Opportunities in time and place - Unauthorised access day and night, limited management, intermittent flow? - Low and higher quality products in the same place: e.g., feed and food, regular eggs and organic eggs, etc. - Overlap of supply chain nodes (all in one hand) - Complexity and transparency of the supply chain network (business relationships ad hoc, price main driver for selection of supplier, no info exchange with suppliers)? - Historical evidence? The worlds food trade grows faster than the food production Chain Analysis Horse meat in 2013 - NL Food Safety Authority To Summarise (Opportunities) Technological opportunities - Complexity of adulteration of your raw materials - Availability of technology and knowledge to adulterate - Detectability = general likelihood of detection Opportunities in time and place - Accessibility of production - Low and higher quality products in the same place - Complexity and transparency of the supply chain network - Historical evidence? Food Investigation Page 11 Lecture 7 - root cause analysis Sunday 10 November 2024 17:10 Learning Outcomes Understand the Routine Activities Theory concept Describe various motivational drivers-related factors and explain why and how they affect food fraud occurrence Distinguish between economic drivers and cultural/behavioural drivers Use the factors to conduct a root cause analysis Economic Drivers Product supply and pricing issues (tight global supply, shortages, export bans, price spikes, large differences in prices of material from different countries, low prices of substitutes)? Special attributes or constituents that determine the value of the materials? Price differences in countries Economic health Level of competition Financial strains Economic drivers - Supply and demand issues Special Attributes - Added value products - Production system origin: Organic chicken breast €30.50/kg, regular €11.40/kg (Tesco)  - Geographical origin: Chocolates/coffee beans of particular origin - Botanical origin: Arabica coffee vs. Robusta coffee - Artisanal production: Cheddar ‘Aldi-match’ €5.70/kg vs. €24.70/kg - Brands: Well-known A brand products vs. unknown products - Specialties: Culinary salt €150/kg vs. table salt €0.35/kg - Specialty wine €1000s/L vs. cheap common bulk wine €8/L Cultural and behavioural drivers - Business strategy - Ethical business culture – fish rot from the head - Previous criminal offences - Corruption level country - Victimization - Personality traits NATURE OR NURTURE? CRIMINOLOGIST CESARE LOMBROSO (1835-1909) He believed that "born criminals" could be identified by physical traits such as asymmetrical faces, large jaws, and excessive body hair, suggesting a link between criminality and evolutionary "atavism." Lombroso's focus on biology placed him on the nature side of the nature vs. nurture debate, asserting that criminal behavior was inherent and not easily changed While Lombroso’s work laid the foundation for empirical criminology, contemporary scholars emphasize that environmental, social, and psychological factors play a critical role in crime, rejecting the deterministic view that criminals are biologically predetermined. Why do we cheat? Economic incentives vs psychological incentives Type of Fraudsters Crisis responders (including ‘loyal employees’) Opportunity takers Opportunity seekers Food Investigation Page 12 Opportunity seekers Professional criminals Leaders in Economic Fraud: Type A - Intelligent - Prone to take risks - Arrogant - Aggressive - Greedy - Decisive Criminology studies: Economic Fraud - 52% middle or senior management - 85% male - 44% aged 31-40 - 38% BSc or up - On average in the company for 7.5 years, highest prevalence in first two years on the job - Risk-takers, decisive, extroverted, career and success oriented Rationalisation Neutralization techniques: before or after the fact - Denial of injury/harm - Denial of victims - Condemning the condemners - Appeal to higher loyalties - Denial/transfer of responsibility - Everybody else is doing it - Conforming Corruption varies with countries SOURCES OF CORRUPTION: CULTURE VS. INTRUSIVE GOVERNMENTS - High income countries generally have low levels of corruption. The high income countries are generally democracies that follow the rule of law and apply it rather equally to all citizens Victimization - Refers to a pattern wherein the victim of crime has a statistically higher tendency to be victimised again - Likelihood crime is committed depends on opportunities, a motivated offender and lack of guardianship converging at a given time and place Routine activities theory This convergence is affected by how daily routines are organised. Some individuals/organisations routinely find themselves in situations where all three factors are present, while others have daily routines which rarely place them in these situations To summarise The theoretical fraud concept presented is based on the RAT and comprises three key elements: Opportunities Motivations Control measures - One has to consider various internal and external (environmental) layers Motivations: Economic drivers - Product supply and pricing issues Food Investigation Page 13  - Product supply and pricing issues - Special attributes or constituents determining value - Price differences in countries - Economic health - Level of competition - Financial strains Culture and behaviour - Business strategy - Ethical business culture - Previous criminal offences - Corruption level country - Victimization - (Personality traits) Food Investigation Page 14 Lecture 8 EC Sunday 10 November 2024 17:11 EU activities in the fight against Agri-food fraud Protecting the integrity of the food chain - Threats to public health - Impacts on legitimate trade - Consumers; confidence - Companies: money - Authorities: credibility Protecting the integrity of the agri-food chain (s) - The EU has a mature and functioning regulatory framework. Enforcement remains (sometimes) a challenge. - Organised Crime Groups have expanded their crime portfolio. - Some industry segments have been found organising fraudulent practices. - The cross-border dimension of fraud is often strong: Member States cannot effectively act alone. - Digital dimension (e-commerce) is increasingly present. Principles and legislation - Operators - ensuring compliance - Food and feed business operators shall ensure that foods or feeds satisfy the requirements of food law and shall verify that such requirements are met. - Competent authorities - “Assuring adequate and effective controls” - Member States shall enforce food law and monitor and verify that the requirements are fulfilled by operators at all stages of production, processing and distribution - Commission - “Guarding the Treaties” - Ensuring that the EU legislation is properly enforced. “External representation” Legal Framework - Regulation(EC) No 178/2002 (the General Food Law). - Regulation (EC) No 767/2009 (the Feed Law). - Regulation (EU) 2017/625 (Official Controls Regulation). - Regulation (EU) 1169/2011 (Food Information to Consumers). - Commission Implementing Regulation (EU) 2019/1715 (IMSOC). - + sectorial legislation. Agri-Food Fraud - Suspicion of intentional actions taken by businesses or individuals for the purpose of deceiving purchasers and gaining an undue advantage therefrom, in violation of the rules referred to in Article 1(2) of Regulation (EU) 2017/625 EU Agri-Food Fraud Network - Liasons bodies designated by member states - European Commission - European union Agency for law - Enforcement cooperation (Europol) Risk-based controls - Appropriate frequencies to identify possible intentional violations of the agri-food chain rules perpetrated through fraudulent or deceptive practices. - Proactive, innovative (“think outside the box”) and targeted approach. - JRC technical report: good practices with key elements of control arrangements (cooperation, risk-based planning, performance of controls, follow-up and investigations, training and skills, awareness raising …). Food Investigation Page 15  awareness raising …). Enforcement - Competent authorities shall take any measure they deem appropriate to ensure compliance … - Member States shall ensure that financial penalties reflect at least either the economic advantage for the operator or, as appropriate, a percentage of the operator's turnover. - The penalties shall be effective, proportionate and dissuasive. Transparency - Obligation to publish relevant information about the organisation and performance of official controls: type and number of controls; cases of non-compliance observed; cases where enforcement measures were taken and penalties were imposed. - Possibilities to make publicly available: the outcome of official controls on individual operators; information about rating scheme systems for operators, based on the outcome of official controls. Whistleblowing - New provisions to protect whistle-blowers to encourage and facilitate the reporting of non- compliance: - procedures for receiving infringements reports and their follow-up; - appropriate protection of the whistle-blower against retaliation, discrimination and any other type of unfair treatment; - data protection of the whistle-blower in accordance with Union and national laws Overview report (2020-2022) Control arrangements and strategies to combat fraudulent practices in 8 Member States Challenges, opportunities, and good practice examples: - Organisation of controls, Strategic and targeted approach, - Investigations, Risk based controls, Planning and Performance, Training, Cooperation and Coordination, Role of other law enforcement authorities… Alert and cooperation Network In 2023 - 4.695 RASFF notifications (food/feed safety related ) - 3.166 AAC notifications (non-compliances without health risk) ' - 758 Agri-FF notifications (non-compliances with suspicion of fraud) - 128 Plant Health notifications (non-compliances with PH risk) International outreach - Guidance on the prevention and control of food fraudElectronic - Working Group created in 2016: (lead USA, EU, UK, China and Iran). - Global, harmonized, consensus-based definition of FF. - (Types of fraud). - Focus on FF prevention and FF vulnerability assessments (rather than only reaction). - Food Fraud virtual workshop/webinar: 8 February 2023 - CCFICS27 (Australia) September 2024 Food Investigation Page 16 Lecture 9 Root cause analysis Sunday 10 November 2024 17:11 Learning Outcomes Understand the Routine Activities Theory concept Describe various control measures and explain why and how they affect food fraud occurrence Distinguish between technological and managerial controls Technological controls - Fraud monitoring system and its verification => Analytical tests in next block of module - Information system (mass balance) - Track and trace system - Contingency plans Different approaches - Detecting fraud when it happens - supply chain controls, reactive - Anticipating fraud before it happens - proactive Technological controls to ensure transparency - Use of data of intrinsic and extrinsic characteristics of the product or production/processing/transport along the chain e.g. Satellite data: GPS data: fertilizer input data: bar codes: processing data: analytical measurement data: audit data Detecting fraud when it happens - Fraud monitoring/ survelliance testing - Traceability - Mass balance data analysis - Audits - Whistleblowing systems New technologies Integration and ai in cloud platforms with decision support structures Blockchain to prevent manipulation later on Managerial controls - Ethical code of conduct - Integrity screening employees - Whistle blowing system - Contractual requirements suppliers - Social control/transparency across chain - Fraud prevention guidance across chain - National food policy - Enforcement food fraud regulations Code of conduct - Is a set of rules outlining the social norms and religious rules and responsibilities of, or proper practices for, an individual, party or organization - Related concepts include ethical, honour, moral codes and religious laws E.g. items included in a code of conduct - The work environment - Conflicts of interests - Protecting company assets - Anti-bribery and corruption Food Investigation Page 17  - Anti-bribery and corruption - Attendance and punctionality - General harassment - Internet use at work, tobacco, etc. … E.g. Statements - Starbucks empowers all partners to make decisions that impact our reputation. Individual actions at work shape how the world views Starbucks, which is why it’s so important that we each take responsibility for Our Starbucks Mission and acting ethically in all situations.’ - ‘Make the Right Call. It’s as simple as it sounds. Whenever you’re faced with a decision— big or small— always do what you know is ethically right, and, of course, always follow the law.’ - Under Armor - The honesty or integrity of individuals can be tested via (pre- )employment screening from employers - Employers may administer personnel selection tests within the scope of background checks that are used to assess the likelihood that employees will engage in dishonest behaviour Whistleblowing - The disclosure by a person to the public or to those in authority, of mismanagement, corruption, illegality, or some other wrongdoing - In a safe environment: So, no firing or laying off, blacklisting, demoting, denying overtime or promotion, disciplining, denial of benefits, failure to (re)hire, intimidation/harassment, making threats, reassignment affecting prospects for promotion, reducing pay or hours Social connections and control - Internal means of control - People conform to norms because they believe they should, even when no one else is present - People are socialised to see themselves in certain way - External means of control - Other in the group utilise pressures or sanctions to attempt to control an individual’s behaviour - Group sensitivity - Fraud often interplays with social connections - (Prevention of) Co-offending, contagiousness - Bonds between economic fraud co-offenders: (1) individual-serving functional bonds, (2) organization serving functional bonds, and (3) affective bonds - In fraud, co-offending carries the risk that the partner reveals the crime - In many cases it is only by building a co-offending group that the opportunity can be accessed - It is unlikely that any one individual has the resources, access and capacity to construct a sophisticated fraud without the assistance of others To summarise Control Measures Technological controls - Fraud monitoring system and its verification - Information system (mass balance) - Track and trace system - Contingency plans Managerial controls - Ethical code of conduct - Integrity screening employees Food Investigation Page 18 - Integrity screening employees - Whistle blowing system - Contractual requirements suppliers - Social control across chain - Fraud prevention guidance across chain - National food policy - Enforcement food fraud regulations Food Investigation Page 19 Lecture 10 Target Methods Sunday 10 November 2024 17:12 Learning Goals - Describe the principles of targeted analysis in food authentication - Identify various methods which are based on a targeted analysis approach - Define the characteristics of methods based on a targeted analysis approach - Summarise advantages and disadvantages of the approach Who are testing? - Food businesses => usually commercial laboratories - Certifiers => usually commercial laboratories - Regulators => usually own laboratories - Academics for research/surveys Targeted techniques - Single/dual target (chemical compounds) that are primary marker(s) for direct authentication through legal limits - Single/dual targets (chemical elements, isotope ratios, metaboloties ect.) that are secondary marker(s) or profiling secondary markers for indirect authentication through threshold value(s) or database comparison Targeted Targets - Primary markers: chemical compounds that often have specific legal limits - Secondary markers: Chemical elements, isotopes, metabolities, chemical breakdown products and derivatives or macromolecules (DNA, lipids, proteins, sugars) evaluated using established and internationally acknowledged threshold values or conversion factors Targeted- key features - Quantitative and/or semi-quantitative - Identification of known adulterants - High selectivity and sensitivity - Extensive sample preparation - Validation often supported by matrix-matched certified reference materials (CRMS) - Information extracted through conventional/univariate statistical analyses or calibration - Control limits are publicly available Different ways of categorisation - Type of fraud - Type of product - Type of marker - Analytical technique for measurement of marker - Type of approach: detection of adulterant/confirmation of a particular aspect of authenticity/general confirmation of authenticity - Lab requirements: basic lab/advanced lab/on site Features of measure and to compare products for food authenticiation - Atomic scale: isotopes, diffference in neutrons - Molecular scale: particular compounds, such as water, fatty acids, proteins, Food Investigation Page 20  - Molecular scale: particular compounds, such as water, fatty acids, proteins, carbohydrates, minor components - DNA structures: molecular biology - Cell structures: microscopy - Bio-activity of group molescules/product: reflectance of light or sound, impedance, resistance Analytical Techniques - Chromatography - Mass spectrometry - DNA-based techniques - Immunology - Physical tests, e.g. DSC - Wet chemistry - Microscopy - Sensor-based technologies - Sensory analysis Compositional fraud - targed/adulterant measurement, Targeted/single marker, non- target/multiple marker/Patterns Geographical origin - Non-targeted/multiple markers/Patterns Production origin - non-targeted/multiple marker/patterns Processing method - targeted/single marker, or non-targeted/multiple marker/patterns Example 1 - moisture in fish - Type of Fraud- water addition - Type of product - fish - Type of marker - moisture content compared to thresholds in guidelines/biological moisture contents - Type of technique - classical wet chemistry, oven drying till constant weight - Type of approach: detection of adulterant )extraneous water) - Lab requirement - basic laboratory Additional of >5% water must be labelled Moisture content fish - Natural moisture content white fish - 80% - This means dry matter content - 20% - If measured moisture content is 90%, dry matter content is 10%. - This means we have 50% fish and 50% extraneous water => manufacturer added 1 kg water to 1 kg of fish… All pangasius samples contained extraneous water Some up to 100% added water No difference between chilled and frozen products -> water added before import to the EU Moisture and chicken fillet imports - 52% of initial controls were exceeding the max limit in 2017 What is Haram? Main Haram Foods - Pork and pork by-products - Intoxicant - Blood and blood by-products Food Investigation Page 21  - Blood and blood by-products - Land animals without external ears (snakes, ants) - Animals improperly slaughtered or already dead Example 2 - Ethanol - Halal certified products - Type of fraud: mislabelling - haram product instead of halal product (ethanol present) - Type of product: any food product - Type of marker: ethanol - Type of technique: various - Type of approach: adulterant detection - Laboratory requirements: basic laboratory / in situ measurement Why ethanol can be found in food? - Added in - Naturally forming - Fermentation by yeasts (e.g. bakery products, beer, wine) Halal food and ethanol - Ethanol content is subjected to varying interpretations by Islamic Food and Nutritional Council of America accepted a level of 0.1% as permissible - Thai-FDA has set 0.5% of added in or natural ethanol as Halal compliant - The Malaysian Islamic Development Department (JAKIM) has established that the amount of ethanol in food in permissible as far as it causes no effects of intoxication Some products exceeding common ethanol thresholds - Bread - Ripe fruits - Juice - Vinegar - Tinned fruits - 'Alcohol free' wine Example 3 - Meat species - Type of fraud: addition of product-foreign material - Type of product: meat - Type of marker: characteristic DNA fragments - Type of technique: Polymerase Chain Reaction (PCR, to amplify small segments of DNA) - Type of approach: confirmation of authenticity/adulteration detection - Laboratory requirements: laboratory DNA- based approach DNA analysis: ThePig Any part of the pig -> Species-specific DNA fragments -> No PCR products: no pig meat -> PCR product Species detection: DNA-based methods - Mammals - Ruminants - Cow - Pig - Sheep - Goat - Chicken - Turkey - Duck - Cod Food Investigation Page 22  - Cod - Hake - Ten snacks from retail outlets: frikandel, croquettes, ‘kipcorns’, meat rolls, etc. - Examined for beef, pork, chicken and turkey DNA - DNA extraction and analysis Example 4 - Saffron - Type of fraud: addition of inferior material - Type of product: saffron - Type of marker: 3 characteristic compounds, individually compared with thresholds - Type of technique: spectrophotometry - Type of approach: confirmation of authenticity - Laboratory requirements: basic laboratory Saffron Standards - Measurement of picrocrocine, safranal and crocine: absorbance at different wavelengths - 3 categories: Saffron I,II,III - Iso standard 3632-1 Other examples - Protein content of milk - Methylglyoxal in Manuka honey - Species detection - 13C isotope ratio for detection of syrups in honey - 3MCPD-ester concentrations in extra virgin olive oil (characteristic of adulterant) - Melamine in milk powders Validation and proof in court - ISO/IEC 17025 General requirements for the competence of testing and calibration laboratories - Standard for which labs must hold accreditation in order to be deemed technically competent in most countries - In many cases, suppliers and regulatory authorities will not accept test or calibration results from a lab that is not accredited - Method validation is the process used to confirm that the analytical procedure employed for a specific test is suitable for its intended use. Results from method validation can be used to judge the quality, reliability and consistency of analytical results; it is an integral part of any good analytical practice Validation Advantages single markers Food Investigation Page 23 Advantages single markers - Methods very suitable for standardisation, validation, accreditation - Broad acceptation Disadvantage of single markers - Limited selectivity - Endless lists of adulterants and thus tests - Usually time-consuming - Usually lab-based - Will not work for production/geographical/processing origin, differences are too small - Fraudsters may anticipate of a well-known test and try to circumvent Food Investigation Page 24 Food Investigation Page 25 Lecture 11 non-target methods Sunday 10 November 2024 17:12 Learning outcomes - Describe the principles of untargeted analysis in food authentication - Identify various methods which are based on an untargeted analysis approach - Define the characteristics of methods based on an untargeted analysis approach - Summarise advantages and disadvantages of the approach Non-targeted/fingerprint methods recognizing patterns - For technologies that generate patterns in general, e.g. vibrational spectroscopy, generally methods based on physical properties - For confirmational of identify: products under investigation versus group of authentic products - For general distinction between good and bad products - For difficult authencity questions where authentic products show only minimal differences from fraudulent products such as with  Product systems (e.g. organic)  Geographical origin  Processing (e.g. raw milk use in farmhouse cheese) Targeted compared to non-targeted techniques: description Non-targeted Techniques - Fingerprinting using unspecified targets or data points for indirect authentication through a database or reference comparison Non-targeted Targets - Unspecified targets or data points (often > 100): provide a fingerprint that is a display of multiple non-target parameters comprising information from an analytical method Non-targeted - Qualitative and/or semi-quantitative - Detection of unknown adulterants - High throughput - Simple or no sample preparation - Validation is more difficult to perform - Information extracted through advanced multivariate statisticial = chemometrics - Control limits relate to specific reference databases Non-targeted Fingerprinting Methods  Generate detailed instrumental fingerprints of the samples tested  Fingerprint denotes characteristic unspecific instrumental signal (i.e., spectrum thermogram, chromatogram, image, acoustic pattern, etc.) from analysed sample which can be related to its unique characteristics/properties  These unique fingerprints form part of the library/ reference database used to authenticate the sample  Multivariate statistics (chemometrics/AI) is used to determine overlap between newly measured sample and database samples gathered previously General Approach - Selection of interesting marker groups - Selection of analytical techniques - Selection/optimation of statistical models Procedure Food Investigation Page 26 Procedure - Sample collection -> sample preparation -> Acquistition data -> Chemometric selection -> development of models -> validation of models Representative Sample set - Ranging of aging - Various processing methods - Number of samples - Range of seasons - Various geographical locations Promising marker group - Proteins - Carbohydrates - Fatty acids - Carotenoids - Flavonoids - Tocopherols - Contaminants - Light reflection - Image sound resonance Analytical technique - LC - GC - Direct MS - IR-MS - ICP-Ms - NIRs - Sound spectr Chemometric technique - LDA - PLS-DA - SIMCA - KNN - ANN - SVM Types of Chemometric models - One class (broad anomaly) models: one (good) versus all (bad) - Two class (binary) models: e.g. organic versus non-organic - Multiple class models: e.g. For different geographical locations Example non-targeted analysis of bean origin in chocolates - The sound of the chocolate can be used to determine the location of the beans - Multivariate data analysis (pattern analysis) showing differences according to the sound energy produced by the different origin chocolates - Consistent differences between chocolates produced from beans or different geographical origins => First step towards method development Advantages patterns/fingerprint approach - Rapid - Can handle complex authentication questions (e.g. origins) - Allows rapid screening for good and bad - Difficult to circumvent by criminals Disadvantages - Needs large database, and robust procedure for development of reliable method Food Investigation Page 27  - Needs large database, and robust procedure for development of reliable method - Complex data processing - Sometimes use of fairly expensive, state-of-art analytical equipment needed - No formal validation protocols yet and therefore of limited value in court Authentical tests in place European businesses - 70% of all businesses- any form of a fraud monitoring system for raw materials in place and -45% for final products - -30% had an elaborate system in place for raw materials Food Investigation Page 28 Lecture 12 chromatography Sunday 10 November 2024 17:12 Learning goals - Describe the principles of chromatography and mass spectrometry - Describe how chromatography and mass spectrometry can be used to detect fraud - Describe a targeted approach using liquid and gas chromatography - Describe a non-targeted approach using the techniques and interpret the data - Critically analyse advantages and disadvantages of the techniques Principles of chromatography - Chromatography is a technique used to separate, identify, and analyze components in a mixture based on their differential affinities between a stationary phase and a mobile phase. - The stationary phase remains fixed, while the mobile phase moves through it, carrying the mixture. - Components interact differently with the two phases depending on their polarity, size, charge, or other properties. - Compounds with a higher affinity for the stationary phase move slower, while those with a higher affinity for the mobile phase elute faster, resulting in separation. - This principle underlies various types of chromatography, such as liquid chromatography, gas chromatography, and thin-layer chromatography Liquid chromatography Liquid chromatography is a technique used to separate and analyze components of a mixture dissolved in a liquid. The process involves passing the liquid mixture (mobile phase) through a column filled with a stationary phase, which is typically a solid or gel. As the mixture moves through the column, components interact differently with the stationary phase based on factors like polarity, size, or charge. Components with a stronger affinity for the stationary phase move more slowly, while those with a weaker affinity move faster, leading to separation. The separated components are then detected and analyzed, often using techniques like UV- Vis spectroscopy or mass spectrometry. Variables for improving separation Selectivity (separation of different peaks), efficiency (width of single peak) - Type of stationary phase (column) - Type of mobile phase (eluent): one solvent or a binary mixture of solvents for instance - To separate strongly retained compounds gradient elution is performed Common LC detectors - Photometric detector - Electrochemical detector - Conductivity detector - Infra-red detector - Mass spectrometry detector - Etc. Food Investigation Page 29 Basic principles of mass spectrometry detector - Conversion of the sample into gaseous ions, with or without fragmentation -> characteriszed by their mass to charge ratios (m/z) and relative abundances - To identify unknown compounds within a sample - To elucidate the structure and chemical properties of different molecules - To determine its abundance - To generate fingerprints (little fragmentation preferred => direct mass spectrometry) A mass spectrometry detector (MS detector) is an analytical tool used to identify and quantify compounds by measuring the mass-to-charge ratio (m/z) of their ions. The basic process involves: 1. Ionization: The sample is ionized, often by techniques like electron impact or electrospray ionization, to produce charged particles (ions). 2. Acceleration: The ions are accelerated into a high-vacuum chamber by an electric field, ensuring they have similar kinetic energy. 3. Separation: Ions are separated based on their m/z ratio using a mass analyzer (e.g., quadrupole, time-of-flight, or magnetic sector). Lighter ions move faster, and heavier ones move slower. 4. Detection: The separated ions are detected, generating a signal proportional to their abundance. The output is a mass spectrum, which displays the m/z ratios and their intensities, allowing identification of compounds based on their unique mass profiles. An example of targeted/single marker analysis - Sudan IV (illegal, carcinogenic dye) in chilli peppers by LC-MS Other examples of single marker analysis - Adulterant measurements: dyes, 5-hydroxymethyl-2-furaldehyde (HMF) for colouring whiskey blends, synthetic additives in organic feed - Single authenticity markers to be measured with LC: - Glucose/fructose/sucrose in honey: Sucrose < 5% naturally, glucose and fructose both present at 30-40%, glucose/fructose ratio ca. 1 - 16-O-Methylcafestol, present in Robusta coffee, absent in Arabica coffee - D-malic acid in apple juice (does not occur naturally) - Glycomacropeptide as marker of whey powder in skimmed milk powder Example of non-targeted analysis - Study on organic eggs - Carotenoids in egg yolk - Natural carotenoids - lutein, zeaxanthin - Feed additives - canthaxanthin, aprocarotenoic ester, citranaxanthin Experiment conducted in farms in the Netherlands, - 24 organic farms - 26 conventional farms, 12 free-range, 12 barn farms, 2 w-3 barn farms Other examples of non-targeted liquid chromatography analysis - Peptide profiling for species authentication - Phenolic profiling for floral origin of honey authentication - Triglyceride patterns of fats/oils for compositional authentication - Profiling of organic acids for botanical origin authentication of juices Gas chromatography - Selectictivity (separation of different peaks). Effienciency (width of singe peak) - Type of stationary phase (column)n - Type of mobile phase (eluent): Gas Food Investigation Page 30  - Type of mobile phase (eluent): Gas - Temperature program of oven Common GC detectors - Flame ionisation detector (FID) - Thermal conductivity detector (TCD) - Electron capture detector (ECD) - Nitrogen-phosphorus detector (NPD) - Mass spectrometry detector Example of single marker analysis - Ethanol content of food products by GC-FID Other examples of single marker analysis - Adulterant measurements: - Methanol at higher concentrations in alcoholic beverages - Excessive levels of particular volatiles that indicate extensive storage (fish/meat) or artificial ageing (wine) or unallowed processing (solvents from extraction in spent that is sold as the original spice) - Single authenticity markers: - Particular fatty acids in fats and oils, e.g. butyric acid in butter - Character impact aroma compounds in spices, e.g. safranal in saffron, myristicin in nutmeg - Phytanic acid as marker of organic milk Examples of non-targeted analysis - Volatiles for the compositional authenticity of spices - Volatiles for the compositional authenticity of vegetable oils - Volatiles for the geographical authenticity of olive oils - Volatiles to determine the varietal authenticity of olive oils - Volatiles for the production system authenticity (organic) of milk - Triacylglycerol and fatty acid composition for the compositional authenticity of oils and fats Advantages of LC/GC - Well established - Good specificity usually - For adulterants and single markers can often be used for confirmation; for this kind of analyses formal validation protocols available (more courtproof) - Combined with MS, identification of compounds feasible - May also be used for non-targeted fingerprinting Disadvantages GC/LC - Requires often (extensive) sample preparation - Analyses are not exceptionally rapid, usually destructive - Instruments generally not portable - Sometimes use of fairly expensive, state of the art analytical equipment needed Food Investigation Page 31 Lecture 13 isotope ratio mass Sunday 10 November 2024 17:12 Learning Goals - Describe the principle of the isotope ratio mass spectrometry (IRMS) method - List the main stable isotopes that are typically analysed & describe what they (i.e. ratios) indicate - Describe how IRMS can be used to detect food fraud - Describe the types of fraud it can detect - Interpret IRMS results Principles - what are isotopes? - Atoms - - Isotopes - atoms with the same number of protons but different numbers of neutrons Stable isotopes - Radioisotopes - are the unstable form of an element that emit radiation to transform into a more stable form -> application in medical diagonstic,ect. Computerized tomography scan (CT) - Stable isotopes are non-radioactive forms of atoms -> trace and track in food systems, ect. Isotope-ratio mass spectrometry Stable isotopes used in food fraud study - C isotope: 13C or 12C - C3 plants - rice, wheat, oats, barley, cotton, peanuts, tobacco, sugar beets, soybeans, and spinach - C4 plants - maize, sugarcane, pearl millet, sorghum - N isotope: 15N, 14N - Chemical fertilizers: -5 to 0% - Organic fertilizers: +10 to 20% Oxygen and hydrogen isotope fractionation is used to unravel geochemical and biochemical processes that occur on earth Some types of food fraud in supply chains: - Geographical region (cheeses, coffee, sugar, fish and animal feeding areas) - Botanical processing (beans, seeds, olive oil, vanilla) - Soil and fertilization processes (fruits and vegetables) - Fraudulent practises (sugar addition to honey, watering of wines and spirits) Food authenticity to finding out where food comes from : geographical origin and production systems Why IRMS in food authenticity? - Global & complex food supply chains - Mainly paper trails ensure traceability & authenticity - IMRs links products to paper/other traceability systems - Used to test: Adulteration and Validation of origin What do these isotopes tell us? - C: 13C and 12C - Diet/Plants: C4 (millet & sugar cane) or C3 (wheat, rice, tubers, fruits, nuts & many vegetables) The photosynthetic pathway used by plants for C fixation affects C stable isotope ratios (δ13C) Food Investigation Page 32 The photosynthetic pathway used by plants for C fixation affects C stable isotope ratios (δ13C) of its tissues - N: 15N,14N - Diet/Soil: N-fixing plants, aridity, fertilizer use etc. H: 2H,1H - Diet/Water: Continentality, altitude, latitude, lower δ-values predictably found in cooler inland & high elevation/high latitude regions (next slide) O: 18O,16O - Same as H S: 34S,32S - Distance from sea/Soil/Diet: δ34S values decrease with increasing deposition of S from fossil fuel combustion, higher δ34S values seen near coastlines How are isotopes measured? Measuring relative abundance of stable isotopes = stable isotope ratio Stable isotope ratios are measured using mass spectrometry Detecting small differences between gaseous elements Separates different isotopes of an element on basis of mass-to-charge ratio IRMS - steps 1. Isolate protein/fat fraction (extraction technique) - Weigh into tin or silver cups - Chemically broken down & injected into a mass spectrometer 2. Release as gas & then used to measure stable isotope ratios - Relative abundance of constituent stable isotopes (how enriched/depleted an isotope is) = measured by deflection through magnetic field - Ratios calculated and compared Results and interpretation Stable isotope compositions expressed in delta values (δ) in permil (‰) (i.e. parts per thousand differences from a standard) Express proportion of an isotope in sample δX = [(Rsample / Rstandard) – 1] × 1000 X represents: isotope of interest (e.g., 13C) R represents: ratio of isotope of interest & its natural form (e.g. 13C/12C) An isotopic signature is the set of ratios between the amount of the various isotopes of an element in a sample. - Higher (less negative) δ values indicate ↑ in sample's isotope of interest, rela ve to standard - Lower (more negative) δ values indicate ↓ - Standard reference materials for C, N & S: Pee Dee Belamnite limestone, N atmospheric gas & Cañon Diablo meteorite, respectively - Standard reference material for water (H, O) is Vienna Standard Mean Ocean Water Results compared to reference database or interpreted based on known ratios Examples: Legal Aspects - Used in certification schemes: If fraud detected, licence is suspended & receives penalty/fine - Used as supportive enforcement action (in court): cross validate with paper traceability or other intelligence to support prosecutions Legal aspects IRMS as evidence, challenge = demonstrate to the court that - Robust databank of authentic samples exist: - Authentic sample is properly defined - Suitable sampling design has been used: - Relevant analytical & metadata has been collected: - Methods used are officially recognized or validates - Instrumentation & reference materials are suitable Food Investigation Page 33  Example: meat - Models can be developed to relate the isotopic compositions of tissues to features of an animal’s history: - What it ate, what it drank & where it potentially lived Stable isotopes assist scientists in analysing animal diets & food webs by examining animal tissues with fixed isotopic enrichment or depletion vs. the diet - Muscle or protein fractions = most common animal tissue used to examine isotopes as they represent assimilated nutrients in diet - Isotope tracers in tissues gives understanding of trophic position (herbivore, omnivore, carnivore) & food source - Can be used to determine: - Provenance/origin – PGI (protected geographical indication), PDO (protected designation of origin) etc. - Diet – organic, free-range, feedlot etc C&N: from diet (plants) animals consume H&O: atoms in food & water are derived from local water sources, the geographic patterns of stable isotope ratios observed in meteoric water are generally reflected in the isotopic, composition of animal tissues Hamburgers purchased in countries with an agricultural history of raising cattle on C4 grasslands or corn-based feed (e.g., Brazil, Mexico, USA) had higher δ 13C values than those purchased in countries where little C4 -plant material was available as cattle feed (e.g., the EU) - Phenomenon = food “glocalization” - Food item available worldwide that appears physically & chemically identical is, in truth, reflecting local food production practices as differentiated by isotope analysis Authenticating Lambs in South Africa - Karoo - diet: herbaceous bushes (c3), arid region - Non-karoo - diet: Lucerne (c3) or grasses (c4), arid region & coastline region Example: organic production - Bulk and compound-specific stable isotope ratio analysis for authenticity testing of organically grown tomatoes - Production system - organic vs conventional Example: honey - Origin & speciality honey – e.g., Manuka - Adulteration – addition of syrup, mix with cheaper honey - AOAC–C4 Sugar Method 998.12 *Values outside normal range => indicate corn/cane sugar syrup addition (corn is C4 plant with higher/less negative & more positive C isotopic ratios; manuka honey has naturally a high level of C4 sugar & isotope ratio indistinguishable from cane/corn syrup Two of the most common types of adulteration of honey involves the addition of invert sugar syrups & mislabelled geographical origin Intrinsic hydrogen stable isotope ratios in honey monosaccharides were measured after conversion to Hexamethylenetetramine. The method offers distinct advantages in terms of ease of use, analysis time for δ 2H and δ 13C measurements. Food Investigation Page 34 Lecture 14 + 15 Spectroscopy Sunday 10 November 2024 17:12 Content - For light (vibrational) spectroscopy and sound spectroscopy - Principles - Types of technology/instruments - Example single marker analysis - Example of fingerprint analysis - Various applications - Pros and cons Vibrational spectroscopy basics - Classical physics considers the atoms as particles with a given mass in the spectroscopic process, and the vibrations of diatomic molecule described as follows (e.g. HCL): Interaction of light with matter - When light hits a sample, it is excited , and is forced to vibrate and move. It is these vibration which we are measuring in spectroscopy Types of vibrations - Symmetrical stretching - Asymmetrical stretching - Scissoring - Rocking - Wagging - Twisting Wavelength and Frequency are both used, what is their relationship? Wavelength (λ) and frequency (f) are inversely related properties of a wave, connected by the wave equation v =f λ, where v the wave's speed. This means that as frequency increases, wavelength decreases, and vice versa, provided the wave's speed remains constant. For example, electromagnetic waves in a vacuum travel at the speed of light (c=3×10^8 m/s), so a higher frequency corresponds to a shorter wavelength. The relationship is fundamental across various wave phenomena, such as light, sound, and water waves, and helps describe how energy and information are transmitted through different media. Electromagnetic spectrum The electromagnetic spectrum is the range of all types of electromagnetic radiation, categorized by wavelength or frequency, from low-frequency radio waves to high-frequency gamma rays. It includes, in order of increasing frequency, radio waves, microwaves, infrared, visible light, ultraviolet, X-rays, and gamma rays. What is happening when we shed infra-red light on matter? - The infrared spectrum of a sample is recorded by passing a beam of infrared light through a sample - When the frequency of the light is the same as the vibrational frequency of a bond between atoms, absorption occurs (resulting in vibrations!) - Analysis of the transmitted light indicates how much energy was absorbed at each frequency or wavelength - This measurement can be achieved by scanning for a particular wavelength range or by measuring the entire wavelength range - Then a transmittance/absorbance/reflectance against wavelength spectrum is generated Food Investigation Page 35  - Then a transmittance/absorbance/reflectance against wavelength spectrum is generated Examples of instruments - NIRS - FT-IR Types of techniques used in food authentication based on vibrational spectroscopy - Near-infrared (NIR) spectroscopy - Mid-infrared (MIR) spectroscopy - Visible light (VIS) spectroscopy - Fourier Transform infrared (FT-IR) spectroscopy - Raman spectroscopy Part 2 Two types of food authentication applicaations - repl Food Investigation Page 36 Lecture 16 Bio Assays Sunday 10 November 2024 17:13 Food Investigation Page 37 Lecture 17 - Bio assays 11 Sunday 10 November 2024 17:13 Food Investigation Page 38 Lecture 18 - Rapid analysis Sunday 10 November 2024 17:14 Food Investigation Page 39 Lecture 20 - Wine authentication in a governmental lab Wednesday 20 November 2024 17:47 Food Investigation Page 40