Mark Woolfe's Posts (880)

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10861241480?profile=RESIZE_710xAlmond flour is a high value product susceptible to adulteration. Brazilian researchers have developed methods for the determination of almond flour adulteration, using near infrared spectroscopy (NIR). Three different portable NIR instruments were evaluated to verify the authenticity of almond flours, and the results were compared with a benchtop FT-NIR (Fourier Transform Near Infrared) spectrometer.  Fifty-four almond flours of different varieties were adulterated with low-cost flours widely consumed in Brazil. Different one class chemometric models were used to analyse the spectra. The classification results achieved 100% sensitivity and more than 95% specificity for samples with adulterant concentration of 5% (w/w) or above. Further analysis by PLSR (partial least squares regression)  models was employed to quantify almond flour purity content.

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This review conducted by an expert group of ILSI (International Life Science Institute) Europe details the numerous activities by authorities undertaken within different regions (Europe, North America, Asia, Latin America, and Africa) to counter food fraud. It defines "food inauthenticity" in terms of misrepresentation of a food within a contractual agreement, and/or misrepresentation of a food within a legal obligation (i.e non-compliance of the law). It also describes the guidance available to the food industry to understand how to assess the vulnerability of their businesses, and implement the appropriate mitigation.

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10846787662?profile=RESIZE_400xThe authenticity and origin of animal-derived foods are important for consumer information and prevention of food fraud. This review examines the current research techniques for verifying the authenticity and origin of animal-derived foods, in particular using stable isotope ratio analysis and spectroscopic techniques coupled with chemometrics. It covers meat, dairy, and seafood products, as well as honey. It also includes the new trend of analysing the inedible parts of animals to verify their origin.

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Addition of cheese whey to raw milk is an extension fraud, and this paper develops a rapid method for its detection. FTIR (Fourier-transform infrared) spectroscopy of milk produces a large amount of data, which can treated by machine learning methods such as classification tree and multilayer perceptron neural networks (MPNN) the two methods used in this study. A total of 520 samples of milk adulterated with cheese whey in concenrations from 1-30% were prepared, and 65 samples were taken as the control. These were stored at different times and temperatures, and analysed by FTIR. A further 520 samples of authentic raw milk were used, and selected components (fat, protein, casein, lactose, total solids, and solids nonfat) and freezing point (°C) were predicted using FTIR, then used as input features for the machine learning algorithms. Performance metrics included accuracy as high as 96.2% for CART (classification and regression trees) and 97.8% for multilayer perceptron neural networks, with precision, sensitivity, and specificity above 95% for both methods. The authors make a caveat on these results that the samples were all prepared from bulk raw milk, not individual milk, whose composition is more variable.

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Netflix's Take on Food Fraud Especially Honey

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Netflix is making a series on food fraud called "Rotten", and the first episode is about the largest food fraud case in the USA on honey fraud. The article by Ireland's National Radio (RTE) looks at the adulteration of Chinese honey sold on the US market, and the ways that  detection of adulterants and origin were avoided.

Read the article about honey fraud, which also contains a link to a trailer of Netflix's "Rotten".

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10844497097?profile=RESIZE_400x The popularity of spelt (Triticum spelta) is growing, and there is a need for a rapid method to authenticate it, and especially to detect adulteration by common wheat. In this study, an attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) method was developed, and combined with orthogonal partial least square discriminant analysis (OPLS-DA). A validation set of spelt and common wheat provided good discrimination between the two cereals. Also, adulterated samples were prepared as an external validation set, and the developed OPLS-DA model identified the spelt-common wheat mixtures as a separate class highlighting its strong predictive power. 

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Definition of Food Fraud Revisited

This paper discusses the definition of food fraud based on an analysis of 53 empirical cases on food fraud investigations conducted at the Netherlands Food and Consumer Product Safety Authority (NVWA). It suggests that the scope of food fraud is widened and encompasses three forms of food fraud: food laundering, fraudulent food enhancement, and facilitative food fraud. Food laundering encompasses the use of illegal material as food, whereas fraudulent food enhancement describes a situation where legal food is value-enhanced through deceitful cost-cutting measures. Facilitative food fraud captures the role of facilitative actors that operate illegally and intentionally for economic advantage. On the basis of this widened scope a modified definition of food fraud is proposed: food fraud is committed by any actor who is intentionally involved in illegal acts for economic advantage, thus causing or facilitating illegal food to be laundered into the supply chain or for food to be fraudulently value-enhanced.

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This study looked at verification of egg production method from organic, free range, barn and caged produced eggs, all of which are defined in EU legislation. A total of 84 eggs were bought from local supermarkets in northern Spain (18 each of organic and free range eggs, and 24 each of barn and caged eggs). The egg contents were homogenised and centrifuged to separate the plasma from the granules, and the UV-VIS-NIR spectra of the plasma measured in a spectrophotometer, and different chemometric models applied to the spectra variables . As two samples were detected as outliers and removed, the 82 samples were divided into two groups: 62 for model calibration and 20 for validation. Spectra analysis with QDA (quadratic discriminant analysis) gave a higher accurate categorisation of the four production systems, with a sensitivity of 100% in the calibration set. The validation set scored 87.5% sensitivity and 94.07% specificity using the visible spectra. 

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The aim of this literature review of 51 scientific papers was to answer the question - "What is the mislabelling rate in seafood products sold on the Italian market?“. Samples were considered mislabelled when the species found by DNA analysis did not correspond with the description on the label. The most sampled seafood taxa were fish (83.8%): mackerels, cods, herrings, flatfishes and jacks were the most represented species. Unprocessed fillet/slice was the most analysed retail form (61.4%), and samples were collected at retail premises (76.5%) in 10 Italian regions. The overall weighted mislabelling rate was 28.4%, with the highest levels of mislabelling reported in samples of jellyfishes, European perch, European grouper, Atlantic mackerel and samples labelled as “spinarolo”, “baccalà” or “palombo”. There were also geographical differences and type of retail channel.

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A collaborative study was undertaken in which five international laboratories participated to determine amino acid fingerprints in 39 authentic nonfat dry milk (NFDM)/skimmed milk powder (SMP) samples. A rapid method of amino acid analysis involving microwave-assisted hydrolysis followed by ultra-high performance liquid chromatography-ultraviolet detection (UHPLC-UV) was used for quantitation of amino acids and to calculate their distribution and amino acid fingerprint. Amino acid fingerprints of authentic NFDM/SMP were compared with those of spiked samples with selected proteins and nitrogen rich compounds (proteins from pea, soy, rice, wheat, whey, fish gelatin, and melamine).The amino acid fingerprints of NFDM/SMP were found to be affected by spiking with pea, soy, rice, whey, fish gelatin and arginine, but not by wheat protein and melamine, which would need to be detected by different methodology. 

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The European Commission's Joint Research Centre (JRC) has published its September 2022 Food Fraud Monthly Summary reporting food fraud incidents and investigations from around the world. These have been kindly represented as an infographic above by our Member Bruno Séchet, and thanks for allowing us to share it with the rest of the Network.

Included in this September Summary, there is also a link to a report about the EU controls on illegal fishing, and how they are weakened by uneven checks and sanctions by Member States.

You can download the full Food Fraud Summary here  

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10837224682?profile=RESIZE_400xThis is Tenet's quarterly publication (Issue 5), which discusses the various methods of tackling food fraud, from food safety and quality legislation, and consumer protection legislation, to contract law and trade practices. It also examines the importance of auditing your suppliers and look deeper into non-party disclosure and ‘Norwich Pharmacal’ orders.

If you work in the food and drinks industry and take an interest in fraud and financial crime impact in the sector, please take a look at the Secret Ingredient -Issue 5.

 

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Herbs and spices are one of the food commodities most susceptible to adulteration and fraud. In this study, 5 fingerprinting techniques - Near Infrared (NIR), Mid-Infrared (MIR), Hyper Spectral Imaging (HSI), Gas Chromatography coupled to Mass Spectrometry (GC–MS), and Proton-transfer Reaction Time-of-Flight Mass spectrometry (PTR-TOF-MS), combined with chemometrics, are examined to evaluate their potential to authenticate oregano. In total, 102 oregano samples from one harvest season were analysed for origin and variety assessment, 159 samples for adulteration assessment, and 72 samples for batch-to-batch control. Different chemometric models were applied for adulteration, origin and variety assessment. The best results were for origin assessment, which gave prediction rates of more than 89%. A level of 10% adulteration of oregano with myrtle, sumac, olive and cistus could be detected using HSI, NIR and PTR-TOF-MS.

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This mini-review examines the use of liquid chromatography mass spectrometry (LC-MS)-based metabolomic and lipidomic methodology to determine metabolites and lipids in pork and beef, which combined with chemometric analysis and comparison with lipid and metabolite databases, serve as authenticity markers. Researchers in this field have found combining metabolomic and lipidomic approaches provides a more comprehensive authentication of meat products especially the differentiation between beef and pork. 

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Cocoa powder is a widely used food and ingredient, and is vulnerable to adulteration by cheaper ingredients.  A non-targeted metabolomics approach based on the use of reversed-phase liquid chromatography coupled to a high-resolution mass spectrometer (HPLC-HRMS) was developed to carry out the characterisation of cocoa powder samples adulterated at two different levels, with carob flour, soya flour, and chicory. The extraction procedure and chromatographic parameters were optimised to obtain the highest number of molecular markers. After chemometric analysis of the data, 21 and 37 metabolites in positive and negative ionisation modes, respectively, were found as potential authenticity and adulteration markers in the cocoa powder samples and simulated samples of adulterated cocoa powder. Of these, the identity of only 16 compounds in negative mode and 4 in positive mode could be determined, and most of these compounds belong to the groups of flavonoids, fatty acids, terpenoids, and lysophospholipids, which were potential markers for cocoa adulteration.

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This study was carried out in Ghana, which has seen an increase in rice consumption, but also an increase in mislabelling and fraud of rice supplies. A rapid assay was developed using a pocket-sized NIR spectrometer and multivariate data for detecting rice integrity and fraud. A total of 112 rice samples were used in the study, made up of three different categories; 36 samples of the Jasmine variety, 36 samples of the Agra variety, and 40 adulterated Jasmine with Agra (10–40% w/w). It was found that powdered rice samples gave better results than rice grains. Chemometric analysis was used to model the best technique for simultaneous identification and quantification of rice variety integrity and adulteration. Spectral analysis by SD-PLSDA (second derivative - partial least squares discriminant analysis) could identify a variety and adulterated samples at 98% in both training and test sets. For quantification of the level of adulteration, Si-PLS (synergy interval - partial least squares) was a promising tool with R2 = 0.94 in both the training and testing sets. However, the authors of the study note that further investigation will be needed to establish whether satisfactory authentication of rice is possible for a wider population of rice samples.

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Wild-caught seafood is vulnerable to illegal, unreported, and unregulated fishing, which often leads to overfishing and destruction of marine environments. A recent study has developed a method to determine the geographical origin of seafood using oxygen isotope (δ18O) composition imprinted in the shells and bones of seafood (δ18Obiomin). This value is determined by ocean composition and temperature rather than the seafood's biology.  Global ocean isoscapes of predicted δ18Obiomin values specific to fish (otoliths), cephalopod (statoliths) and shellfish (shells), and a fourth combined “universal” isoscape, were evaluated in their ability to derive δ18Obiomin values among known-origin samples. After validation and testing of the method, it was  demonstrated that this global isoscape can be used to correctly identify the origins of a wide range of marine animals living in different latitudes. After removing tuna species from the analyses, a prediction rate of up to 90% in classifying fish, cephalopods, and shellfish between the tropical waters of Southeast Asia and the cooler waters of southern Australia was obtained. Further research is planned to incorporate other chemical markers into improving the prediction of geographical origin. 

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A Practical Guide to Food Analysis

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Analytical testing at every step along the global supply chain is essential to ensure food safety, authenticity, quality and regulatory compliance and is an important component in a factory’s FSQMS (Food Safety and Quality Management System). This paper provides guidance for factory regulatory and technical managers on the basic principles behind the analytical strategies and procedures commonly used to test products in the food and drink industry. It is written by Sterling Crewe, who is Chair of the Food Authenticity Network's Board. The paper discusses the importance of choosing the right method and laboratory, and taking into account the method uncertainties and any regulatory considerations in the interpretation of the results.

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Coffee bean quality is measured on a decimal scale from zero to 100, and a speciality coffee must score 80 or more. This Q-scale allows buyers to differentiate premium coffee from lower scoring ‘commodity’ coffee. Samples of raw beans are sent to three expert tasters, who prepare coffee from each batch, and score it to determine its Q score. Brazilian researchers have developed a rapid method based on MSI and AI (artifical intelligence), which can obtain a Q score avoiding human error. Although very promising, the technique requires further research as the model cannot determine whether beans score is 80 or 90, which would require further calibration with coffee beans having these Q scores. 

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This review examines the potential of non-targeted metabolomic analysis to assess food authenticity. It looks at range of products, which includes wine, rice, olive oil, spices, and honey because they are regarded as the most vulnerable to fraud. The identification of biomarkers  for geographical origin is central theme of the review.

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