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In this study (open access) the authors report the development of a simple point-of-use extraction system and spectral imaging protocol.  It has potential as a point-of-use food inspection tool to check for species adulteration in processed meat.

Samples were macerated (approximately 200 mg) in 500 μL of sterile saline (0.9%). The extract was centrifuged. 2 μL of the supernatant from each sample was used to obtain the UV-Vis spectrum (180–800 nm; 0.5 nm intervals).

30 samples of each of four species (beef, pork, chicken and pacu fish) were used to develop and validate a classification model. Spectral data were preprocessed using standard normal variate transformation and analyzed using principal component analysis.  The authors report that this revealed distinct clustering, particularly for beef. Support vector machine algorithms were trained, achieving an overall accuracy of 89.3% in leave-one-out cross-validation and 86.1% in external validation.

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The UK Parliamentary Committee on Environment Food and Rural Affairs published their latest report on border checks of imported meat earlier this month.  The report is driven by biosecurity and disease control concerns but is also relevant to illegal food trade.

The Committee is critical of the organisation and effectiveness of biosecurity checks currently in place in UK ports, and of a lack of central co-ordination.

They report that responsibility for tackling illegal meat imports is divided across Government departments, enforcement agencies and local authorities. They found no strategic approach coordinating efforts and no leadership figure spearheading operations. This has been the case under successive governments. 

The committee's view is that the stated UK approach of “intelligence led checks” obscures the reality on the ground: a limited and incomplete intelligence network, strained enforcement capability, and port facilities unsuitable for seizing significant volumes of potentially contaminated meat

It is the Committee’s view that the UK has avoided recent disease outbreak from illegally imported meat by luck rather than design.

The authors of this study developed a targeted proteomics approach using LC–MS/MS and cross-species marker peptides with the potential to quantify meat in vegan and vegetarian foods. The method is designed to achieve the threshold of 0.1% w/w that is commonly applied for unintended cross-contamination.

 Protein extraction and digestion were optimized for rapid, simplified, and highly efficient sample preparation. Three matrix calibrations (0.1–5.0% w/w meat, each) were applied to vegan sausages and burger patties spiked with pork, chicken, or beef meat. The four markers DFNMPLTISR, DLEEATLQHEATAAALR, IQLVEEELDR, and LDEAEQLALK showed the highest accuracies for the determination of meat contents (recovery rates of 80–120%).

Although purchase is required for the full paper (here) the work builds upon previous publications and this supporting information is available free of charge (following the same link).  This includes detailed description of the statistical analysis; meat marker peptides before and after their re-evaluation; pea marker peptides; details of the LC runs; base materials and further ingredients for the vegan sausages and vegan burger patties; defatting/dehydration efficiencies of PLE and in-tube defatting/dehydration; comparison of extraction buffers and trypsin concentrations (matrix: vegan sausage with chicken meat); properties and comparison of different trypsins; chromatograms of the meat marker peptides from different matrixes; linear regressions derived from the quantifiers of the meat marker peptides in different matrixes; trueness and precision; mean signal-to-noise ratios at given meat contents.

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Mechanically Separated Meat (MSM – sometimes called Mechanically Recovered Meat, MRM) must be declared on-pack if used in meat products.  Testing for undeclared MSM can be a significant analytical challenge.  Traditional official control methods rely on microscopy, which requires experienced interpretation and can be highly subjective. 

This paper (open access) builds upon previous published work from the same researchers to develop targeted LC-MSMS methods that are suitable for official control applications..

In contrast to a comparable study on MSM from poultry, the authors report that the use of cartilage/intervertebral disc material was not useful for porcine MSM. They therefore report a new marker protein from porcine MSM, protegrin-4, which allows the detection of 5/3/1 mm MSM. The validity of the developed assay was ensured by the investigation of 182 blinded samples. After unblinding, all samples containing 5/3/1 mm MSM and all negative control samples were correctly classified. Additional new results related to the investigation of the species specification of chicken, turkey, and pork also are presented.

They concluded that LC-MS/MS-based detection of of undeclared MSM has been successfully extended from poultry to porcine MSM. The assay was successfully transferred to a triple quadrupole LC-MS system to facilitate routine use.

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This paper (open access) introduces the workflow MEATiCode, a comprehensive proteomic liquid chromatography tandem mass spectrometry (LC-MS/MS) method for the simultaneous identification of species in meat authentication.

This novel database search approach enabled the differentiation of meat species (as demonstrated for beef, pork, chicken and lamb) in raw and cooked food products following a simple sample preparation procedure and LC-MS/MS analysis of extracted meat peptides.  Peptides and proteins were characterised from reference samples using an untargeted protocol.  The MEATiCode database was then constructed in the Mascot Server search engine, with the objective of creating artificial proteins comprising the concatenated amino acid sequences of the peptides identified as specific for each species.

The authors report that the efficacy of the MEATiCode method was demonstrated through its application to a range of meat products, achieving high sensitivity (0.5 % Limit of Detection (LoD)) and reliability in the detection of adulteration, even in highly processed or cooked meats.

In this study (purchase required) the researchers used bioinformatics methods to identify specific sequences of cattle, pig, chicken, and duck, and designed primers and probes accordingly.

They developed a method based on recombinase polymerase amplification (RPA) combined with lateral flow dipstick (LFD) for rapid visual authentication of beef and beef products. The RPA reaction was conducted at 37℃ for 20 min. The amplification products were then diluted and applied to the sample pad of the LFD. Results were visible to the naked eye within 5 minutes.

They report that the results demonstrated the method could specifically differentiate components of bovine, porcine, chicken, and duck origin, with a limit of detection (LOD) of approximately 20 copies for each species.

They applied the method to 10 commercially available beef products. Of which, five samples were detected with porcine-derived components. The results of the RPA–LFD method were verified using PCR and observed to be consistent between the methods.

The researchers conclude that this method is easy to use, requires no specialized equipment, and delivers results in about 30 min from amplification to detection, making it suitable for rapid visual detection on-site.

In this study (open access) the authors made a reference dataset of comminuted meat mixtures by dicing and mixing 140 commercially-purchased steaks of beef, duck and chicken.  They built a classification model to discriminate between the three species in the mixtures.

They used a hand-held Hyperspectral Imaging (HSI) (with a Raspberry Pi controller, which has real-time image acquisition and processing covering  a spectral range from 400 nm to 800 nm) to develop a discrimination model for chicken/duck adulteration in diced beef. The portable push broom HSI was designed with the spectral resolution of 5 nm and spatial resolution of 0.1 mm. To improve generalization, a model transfer method was also developed to achieve model sharing across instruments

The authors report that their model transfer method can effectively correct the spectral differences due to instrument variation and improve the robustness of the model. The support vector machine (SVM) classifier combined with spectral space transformation (SST) achieved a best accuracy of 94.91%. Additionally, a visualization map was proposed to provide the distribution of meat adulteration.

They conclude that the portable HSI enables on-site analysis, making it an invaluable tool for various industries, including food safety and quality control.

Impedance is a complex Cartesian function describing the difference between an inputting and exiting sinusoidal electrical signal.  It can be depicted graphically as a plot (vector) of resistance vs reactance.  The linearity of this plot, and the angle of the vector, are distinctive.  In a sample of meat or fish, impedance is affected by the cell structure and the water content.  Both of which are an indicator of freshness.  An impedance sensor, comparing the result with a “normal” database, can therefore be used to detect unfresh meat or meat that has been prior frozen and defrosted without declaration.

This review (open access) describes published applications, comparing the technique with other approaches such as HADH Enzyme measurement (see FAN method explainers).  It concludes that the development of Impedance Sensor methods is now at a stage where the technique is ideal as a cheap, non-destructive inline check in the food industry, particularly if coupled with machine learning to spot unusual or anomalous samples.

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Water-injected meat leads to microbial growth risk, as well as being economic fraud.

In this study (purchase required) the authors designed and tested a colorimetric porous polymer microneedle patch to detect added water.  Microneedle patches consist of hundreds to thousands of tiny needles, usually only tens to hundreds of microns long, which can extract tissue fluids and transport the extracted molecules to the backing layer for colour displaying. There is no need for sample preparation and often no need to open the packaging.

In this case, detection was designed and prepared using photopolymerization of an acrylate monomer with a porogen substrate and cobalt (II) chloride as colour change indicator and tartrazine as the reference. The colour of the microneedle patch changed from green to yellow with increased moisture concentration.

The authors reported that this discoloration trend of the microneedle patch during the moisture measurement of meat was very regular. The moisture measurement of meat in range of 66.9 %–75.7 % exhibited a good linear dependence on RGB values. The results indicated that the microneedle patch can visually determine the moisture content of meat in 3 minutes. It can be combined with a smartphone as a quantitative reader.

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A study conducted by Universidad Nacional Autonoma de Mexico (UNAM) researchers found traces of dolphin meat in three out of 15 samples of tuna cans on sale in Mexico. 

Lead researcher Karla Vanessa Hernendez Herbert used DNA probes with polymerase chain reaction (PCR) to identify dolphin meat adulteration.

The full report has yet to be published in a journal, but the Herbert and Professor Francisco Montiel Sosa disclosed the results in an interview with Mexican newspaper, Excelsior. The original article can be read here in Spanish., or a summary of the article from SeafoodSource can be found here.

Animal origin food products, including fish and seafood, meat and poultry, milk and dairy foods, and other related products play significant roles in human nutrition. However, fraud in this food sector frequently occurs, leading to negative economic impacts on consumers and potential risks to public health and the environment. Therefore, the development of analytical techniques that can rapidly detect fraud and verify the authenticity of such products is of paramount importance.

Traditionally, a wide variety of targeted approaches, such as chemical, chromatographic, molecular, and protein-based techniques, among others, have been frequently used to identify animal species, production methods, provenance, and processing of food products. Although these conventional methods are accurate and reliable, they are destructive, time-consuming, and can only be employed at the laboratory scale. On the contrary, alternative methods based mainly on spectroscopy have emerged in recent years as invaluable tools to overcome most of the limitations associated with
traditional measurements. The number of scientific studies reporting on various authenticity issues investigated by vibrational spectroscopy, nuclear magnetic resonance, and fluorescence spectroscopy has increased substantially over the past few years, indicating the tremendous potential of these techniques in the fight against food fraud.

This manuscript reviews the state-of-the-art research advances since 2015 regarding the use of analytical methods applied to detect fraud in food products of animal origin, with particular attention paid to spectroscopic measurements coupled with chemometric analysis. The opportunities and challenges surrounding the use of spectroscopic techniques and possible future directions are also be discussed.

Read full paper here.

Researchers in Ireland have published a paper which discusses current and evolving techniques to determine geographical origins of meat. The paper explores applications of meat authenticity techniques including spectrscopy, stable isotope ratio analysis, and the measurement of compounds derived from the animals' diets. The authors also discuss challenges in interpretation of the data.

Read the abstract here.

A new meat species authentication method designed for Halal food verification has been developed by scientists at the University of Münster, using a  SCIEX QTRAP^® 6500 LC-MS/MS system. BusinessWire reports that the method that can detect multiple species simultaneously.

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