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10929285292?profile=RESIZE_584xThis paper describes a new non-targeted method (NTM) for distinguishing spelt from wheat, which aids in food fraud detection and authenticity testing. A spectral fingerprint was obtained for several cultivars of spelt and wheat using liquid chromatography coupled high-resolution mass spectrometry (LC-HRMS). Neural network (CNN) models are built using a nested cross validation (NCV) approach neural network (CNN) models are built using a nested cross validation (NCV) approach by appropriately training them using a calibration set comprising duplicate measurements of eleven cultivars of wheat and spelt, each. The CNNs automatically learn patterns and representations to best discriminate tested samples into spelt or wheat. The method was validated using artificially mixed spectra from samples of processed spelt bread and flour, comprising of eleven untypical spelt, and six old wheat cultivars, which were not part of model building. The results showed that based on the same chemometric approach, the non-targeted method is reliable enough to be used on a wider range of cultivars and their mixes.

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10929257069?profile=RESIZE_710xFood Traceability 4.0 refers to the application of fourth industrial revolution (or Industry 4.0) technologies to ensure food authenticity, safety, and high food quality. This paper gives an update on the application of Traceability 4.0 in the fruit and vegetable sector, focusing on relevant Industry 4.0 enablers, especially Artificial Intelligence, the Internet of Things, blockchain, and Big Data. Traceability 4.0 has significant potential to improve quality and safety of many fruits and vegetables, enhance transparency, reduce the costs of food recalls, and decrease waste and loss. A barrier to its implementation is that most of the advanced technologies have not yet gone beyond the laboratory scale, and hence have high implementation costs and lack of adaptability to industrial environments.

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10929046069?profile=RESIZE_400xHoney is classed as one of the food most susceptible to extension, adulteration and fraud. This review in the Journal of Apicultural Science examines the most used analytical methods for verifying the geographical and botanical origin of honey. These include long established melissopalynological analysis, the analysis of the mineral profile or chemico-physical parameters, to the current state-of-the-art technologies and methods including the metabolomic and genomic approaches, the blockchain or Internet of Things. The review discusses the advantages and limitations of these methods, and highlights the approach that many methods are used in combination because a combined approach usually leads to greater accuracy. 

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Review on the Authenticity of Tequila

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Tequila is a distilled spirit made from the blue agave plant, and its authenticity and traceability are usually determined by inspection carried out by the Mexican Tequila Regulatory Council. This review looks at the alternative means of authenticating Tequila with analytical methodology, and gives a critical analysis of the available techniques.The use of isotopic ratios stands out as the most robust technique, because it establishes the type of sugar source used and the maturation time of the manufacturing process.

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The purpose of this study is to show how authenticity limits businesses’ responses to competition in the food and drink sector.  The results of the study were based on a unique dataset of over 300 small- and medium sized breweries, and more than 1,300 beer drinkers in Franconia (Germany) to test the impact of authenticity on breweries’ reactions to competition within geographic communities. The results reveal that breweries tend to enlarge their product portfolio by introducing non-authentic products as a response to competition in geographic communities, while reducing their product diversity and engagement in non-authentic segments when preferences for authenticity prevail in the geographic community. Furthermore, in geographic communities where both  competition and preferences for authenticity are present, companies tend to keep their product portfolios narrow and withdraw non-authentic products even when product proliferation strategies would be more efficient to deal with competition.

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Walnut oil (WNO) is a high value vegetable oil with high nutritional value. This study developed a method based on excitation–emission matrix fluorescence (EEMF) spectroscopy coupled with chemometrics and ensemble learning to authenticate WNO, and semi-quantify the adulteration with other vegetable oils. A total of 711 vegetable oil samples were analysed by EEMF of which 426 samples were pure WNO. The classification models were established by chemometrics and ensemble methods. The ensemble methods achieved better classification performance, and PLS (partial least squares) regression was applied to semi-quantify the adulteration levels of walnut oil, especially with rapeseed oil (RSO).

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Cinnamon is a highly traded global spice, and commercial cinnamon (Cinnamon cassia) is often fraudulently replaced by other varieties (Cinnamomum zeylanicum, Cinnamomum loureirii, Cinnamomum burmanni). In this study, a miniaturised device which used three different  spectroscopic techniques, namely, ultraviolet–visible (UV–Vis), near-infrared (NIR) and fluorescence (FLUO) spectrometry was tested to authenticate cinnamon samples. After chemometrics were applied to the spectra, a correct classification rate by variety of 89%, 90% and 89% for UV–Vis, NIR, and fluorescence spectroscopy, respectively, was observed. 

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Definitions for food fraud and related terms

10918091489?profile=RESIZE_710xDefinitions for Food fraud and related terms from this report, funded by Defra, FSA and FSS, published last year, have been added to a new 'Definitions' page in the Food Fraud Prevention section of this website.

A 'Standardisation' page has also been created, which summarises global standardisation initiatives on food authenticity.

 

 

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The Chinese Meat Research Centre has compiled 1,817 reports of fraud and adulteration in the meat and meat products sector recorded by the national and imported food inspection services, as well as media reports between 2012 and 2021. The study covered fresh and frozen livestock, poultry, and various processed meat products. The 1,817 reports of fraud/adulteration can be broken down by 670(33.72%) cases from domestic information of official sampling inspections, 773(38.90%) cases were from imported meat and meat products rejection notifications, and 544(27.38%) cases were reported by the media. The study breaks down the cases into the individual types of fraud including artifical enhacement (adding unapproved additives to enhance the quality of meat/meat products), substitution (substituting original or labelled meat with spoiled meat or by-products, or other meat species),  mislabelling (including missing information, changing durability dates), counterfeiting branded products, dilution (adding water usually by injection), illegal imports (no health or origin certification), and certification fraud (health certificate forgery or alteration). The study revealed that the highest number of fraud cases was by artifical enhancement, followed by illegal imports, and then substitution, the total of which accounted for 97% of fraud cases.

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10914584678?profile=RESIZE_584xThe Innovate UK programme Analysis for Innovators (A4I) is a very different type of programme from Innovate UK. It is focused on helping individual companies to solve tricky and, perhaps, long running technical challenges, affecting existing processes, products, or services. A4I works with companies from sectors ranging from healthcare to the food and cosmetics sectors.

The National Measurement Laboratory (NML) is a founding partner of the A4I Programme and is the UK’s designated institute for chemical and bio-measurement, supporting the work of the Government Chemist.

Through A4I, we provide companies with access to our state-of-the-art measurement and analytical capabilities, helping them address problems and challenges in innovative ways, boosting their competitiveness and productivity. Other partners include, National Physical Laboratory (NPL), the National Engineering Laboratory (NEL), the Science and Technology Facilities Council (STFC), Advanced Sustainable Manufacturing TechnologiesHenry Royce InstituteNational Gear Metrology LabNational Institute for Biological Standards and ControlNewton Gateway to Mathematics

If you are new to the Programme we encourage you to watch the online A4I briefing here

Analysis for Innovators (A4I) Round 9 – Stage 1

Opens: 07/11/2022 Closes: 04/01/2023

Do you have a question for the NML? email us here

For more information about the Programme and how to apply, please visit the A4I website

 

 

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FoodBioSystems Doctoral Training Partnership (DTP) brings together six university partners: University of Reading, Cranfield University, University of Surrey, Queen’s University Belfast, Aberystwyth University, and Brunel University London.

Project title: Developing next-generation portable rapid tests for food authenticity
Project No: FBS2023-08-Campbell-qr
Lead supervisor: Katrina Campbell, Institute for Global Food Security, Queen's University Belfast
Email: katrina.campbell@qub.ac.uk
Co-supervisors:
Alexander Edwards, University of Reading, Adrian Rogers, Bio-Check (UK)

Deadline for applications: Monday 30 January at 10.00 am (GMT)

The aim of this PhD is to develop a simple effective diagnostic test for the simultaneous multiplex analysis of different animal species for example cow, sheep, porcine, turkey, chicken, equine, donkey and goat that can be used for field-based analysis.

The student will explore the feasibility of adapting current lateral flow immunoassays using several recent developments including, for example:

  • improved fluidic configurations;
  • smartphone readout using bespoke low-cost illumination systems;
  • multiplexing using different combinations of microfluidics.

These innovations will be explored alongside biorecognition element design and assay development for the industrially- and public safety-driven targets.
The PhD conducted mainly at Queen's University Belfast will offer placements at Reading University for biotechnology design and is supported by an industrial partner BIO-CHECK UK who will bring further insight into practical constraints of cost-effective mass-manufacture, marketing and basic business skills for the student.

By applying analytical science to this specific problem, the student will be able to systematically optimise assay performance, at the same time as recognising the pathway to real product development through industrial oversight.

Further information can be found here

For more information about DTP, the selection process and what its like to be a DTP student, join their Applicant Webinar on 11 January 2023 (17:00 GMT). Please complete the registration form if you would like to attend.

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 10913966273?profile=RESIZE_584xThe U.S. Food and Drug Administration (FDA) conducted a survey of imported honey for exogenous sugars in 2021 and 2022. More than 70% of the honey consumed in the U.S. is imported. From January 2021 to March 2022, the FDA collected and tested 144 samples from either bulk or retail packaged shipments labelled as “honey”, to determine whether they contained undeclared added sugars. About 40% of the samples originated in India and Vietnam, the top two sources of honey imported by the U.S. The analysis used was the AOAC method for C4 sugars (cane sugar and corn syrups). Of the 144 imported samples collected and tested, the FDA found 14 (10%) to have carbon isotope values  atypical of authentic honey, and were considered non-compliant. When the FDA found a sample to be non-compliant, it refused entry of the shipment into the U.S. and placed the associated company and product on Import Alert, which means that for those products to be admitted into the U.S., the company is required to provide evidence to the FDA to overcome the non-compliance, such as the test results of a third-party laboratory, verifying that the product does not contain added sugars.

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UK Measurement Strategy 2022 is published

10913869075?profile=RESIZE_710xThe National Measurement System (NMS) is an essential part of the UK’s research and innovation infrastructure that is critical for science, innovation and trade.

This strategy describes how the UK will capitalise on its world-leading National Measurement System from during the 2020s and beyond.

The National Measurement System will focus on three challenges where enhanced measurement capability and expertise will support the UK:

  • the health and wellbeing of a growing population
  • managing and reducing our environmental impact
  • increasing prosperity and supporting innovation.

The UK Department for Business, Energy and Industrial Strategy (BEIS) funds the NMS. The NMS, via the Government Chemist, contributes funding for the Food Authenticity Network.

 

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10913775301?profile=RESIZE_584xOur Advisory Board Member Dr John Spink has developed the new Food Fraud Prevention section of the Handbook for Safe Processing of Nuts (4th Edition), published by the Peanut and Tree Nut Processors Association (PTNPA).

The peanut and tree nut products are both finished goods and raw material food ingredients that impact nearly the entire food supply chain.

Food Fraud Prevention Section Detail

This section has been created as a stand-alone, comprehensive overview and guide for the PTNPA members to address food fraud prevention.

The food fraud prevention section emphasizes the food fraud vulnerability assessment (FFVA) concepts and application: “One of the most important steps is calibrating the FFVA with all other food safety and enterprise-wide risks. The food fraud problems should not be ranked only versus the other food fraud problems. The same likelihood and consequence ranks, and the same enterprise-wide risk tolerance should be used. It is possible that most of the food fraud problems fall below the enterprise-wide risk tolerance.”

To reduce confusion, it is important to understand that food fraud prevention should be a part of food integrity (Figure).

Figure: Hierarchy and Relationship of Food Fraud Related Terms with the Addition of Food Protection, Food Integrity, Food Authenticity, Social Responsibility, and Food Security

A practical application is presented in terms of the Food Fraud Vulnerability Assessment two-stage approach of “Food Fraud Initial Screening (FFIS)” and then a more “detailed assessment” is conducted, as needed.

Without a Food Fraud Management System, no food fraud prevention activity would be complete. This handbook provides a step-by-step approach for completing a Vulnerability Assessment and Critical Control Point Plan (VACCP). This utilizes the Food Fraud Prevention Cycle (FFPC). The section concludes with a practical method for “Implementing a Management System” and “Integration into the Food Safety Management System.”

Reference (Free document): PTNPA, Peanut and Tree Nut Processors Association, Handbook for Safe Processing of Nuts (4th Edition), URL: https://cdn.ymaws.com/www.ptnpa.org/resource/resmgr/industry_information/2022/industry_handbook_oct22.pdf

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The Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture began a coordinated research project in November 2013 which finished in September 2018, on "Accessible Technologies for the Verification of Origin of Dairy Products as an Example Control System to Enhance Global Trade and Food Safety". Nine countries took part in the project, and the report reviews the studies done in each of these 9 countries (Argentina, Bangladesh, China, Lithuania, Morocco, Russia Federation, Slovenia, Sri Lanka, and Singapore) which demonstrates the successful use of stable isotope and trace element analysis, sometimes using other nuclear and complementary techniques to verify the origin of dairy products. The project generated 17 peer reviewed publications, and the report consists of  the main publications from each of the 9 countries on dairy products, which have resulted directly from the research undertaken in the coordinated research project. The paper from China in the report deals with the verification of organic pork from conventional pork. 

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Saffron is a high value spice and hence susceptible to adulteration and fraud. In this study, a machine vision system based on smartphone image analysis and deep learning was used to detect saffron authenticity and quality. A dataset of 1869 images was created of 6 types of saffron/adulterants including: dried saffron stigma using a dryer; dried saffron stigma using pressing method; pure stems of saffron; sunflower; saffron stems mixed with food colouring; and corn silk mixed with food colouring. The deep learning system developed for grading and authenticity determination of saffron in images captured by smartphones and applied to these images, was a Learning-to-Augment incorporated Inception-v4 Convolutional Neural Network (LAII-v4 CNN). After applying further data augmentation and comparison against regular CNN-based methods and traditional classifiers, the results showed that the proposed LAII-v4 CNN approach gave an accuracy of 99.5%.

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Seafood species substitution is one of the most common types of fraud.This study aims to develop new assays based on DNA to identify fresh mackerel (Scomber spp.) and mackerel species in canned products. Primers were designed to identify a DNA mini-barcoding region suitable for species identification of 4 commercial mackerel species Scomber scombrus,Scomber japonicus,Scomber colias, and scomber australaticus in processed products. Also a new assay based on RPA coupled with the lateral flow visualisation was developed for the identification of the most expensive species of fresh mackerel (Scomber scombrus).  

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10909403488?profile=RESIZE_584x A printed edition of a Special Issue on Novel Analytical Methods  for Food Analysis has just been published, which contains reprints of articles that have been published online in the open access journal "Foods". There are four articles in particular with relevance to food authenticity: 

  1. Assured Point of Need Food Safety Screening: A Critical Assessment of Portable Food Analysers
  2. Suitability of High Resolution Mass Spectrometry for Routine Analysis of Small Molecules in Food, Feed and Water for Safety and Authenticity Purposes: A Review
  3. Vibrational Spectroscopy Coupled to a Multivariate Analysis Tiered Approach for Argentinean Honey Provenance Confirmation
  4. Food Authentication: Identification and Quantification of Different Tuber Species via Capillary Gel Electrophoresis and Real-Time PCR 

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10909126099?profile=RESIZE_584x A joint German government and industry project (QSPEC) is developing a new generation of analytical instruments with a sensitivity almost comparable to NMR, but at a much lower cost based on new laser sources which generate quantum frequency combs.

The research is developing instrumentation based on a method that uses entangled photons to measure the substance to be analysed at one wavelength, and detect the information obtained from it at another wavelength. The first step is to generate an entangled photon pair consisting of a long-wavelength and a short-wavelength photon. The long-wavelength photon now interacts with the sample, changing its phase, and then the manipulated photon pair is then fed into another process in which yet another photon pair is generated, giving rise to quantum interference and a spectrum based on the bandwidth of the photon pairs. The short-wavelength photons act as carriers of compositional information. The resulting spectra gives a fingerprint of the food, and its authenticty can be determined by comparing this spectra with those from a dataset of authentic samples.

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