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This article (open access) is an early publication of a paper that has been through peer review but not yet through journal typographical editing.

During 2019-2021, a total of 78 samples of fish products from national and international brands were.collected from supermarkets, fishmongers, and other local retail stores in the Apulia region (Southern Italy).  They were tested using PCR and DNA barcoding.

The authors report that 5 of the 78 samples were fraudulently labelled.

They also discuss the role of DNA barcoding, challenges with processed fish products, and the pros and cons of different public databases (BOLD and BLAST).

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This study (open access) tested 119 commercial products of insect flour, composite food and animal feed using two DNA-based methods, real-time PCR and metabarcoding, to check whether the insects claimed on the packaging were actually present.

The headline result is that 50% of the products contained insect species not listed on the label, or lacked the species that were declared. The detailed results are explained within the article and there are not always clear-cut interpretations (particularly for feed, where – for example -  it is not illegal to fail to declare all protein species within a pet food recipe).  However, some trends were clear.

• Many producers are unspecific about species identification, using general terms such as “cricket” which do not differentiate between legal and non-legal species
• Cross-contamination between different insect species is endemic
• Regulatory test methods (PCR) are not fit to tell whether the banned practice of rearing insects on substrate containing meat/bone has been used (because the method will also detect, for example, permitted animal-derived substrates such as egg shell)

The authors conclude that traceability and cross-contamination control needs to be improved in this nascent industry, before insects become mainstream, to avoid loss of public trust.

Isothermal amplification techniques offer an alternative to “classical” PCR and are more suitable to point-of-use technology.  For a general overview, see FAN’s analytical method explainers.  Recent advances have enabled the development of microfluidic chip platforms, which integrate micro-scale channels, pumps, chambers, valves, and sensors onto a single substrate for fluidic control. This integration enables simultaneous sample pretreatment, component separation, detection, and biochemical analysis on a single platform.

Recombinase polymerase amplification (RPA) is an isothermal method that has gained attention due to its low instrument dependency, high sensitivity, and rapidity. RPA reactions can be conducted at near-ambient temperatures (37–42 °C) within 20 minutes, and results can be interpreted via fluorescence signals or lateral flow dipstick by incorporating sequence-species probes. The exo probe, typically 46–52 nucleotides in length, is widely used in real-time RPA detection. The design of primers and exo probes in RPA assays offers potential for seamless integration with microfluidic chip platforms.

In this study (purchase required) the researchers integrated RPA into a microfluidic chip to develop an assay for identifying commonly marketed codfish species prone to adulteration: Atlantic cod (G. morhua), sablefish (A. fimbria) and toothfish (D. eleginoides and D. mawsoni).

They reported that the assay demonstrated high specificity and sensitivity, with detection limits of 10 copies/μL recombinant plasmid or 10³ fg/μL genomic DNA. Application to 141 commercial seafood products resulted in 100 % identification accuracy for the three target species, and revealed a 32 % inconsistency between product labels and genetic identities, involving substitutions with Pacific cod, pollock, and other species.

They conclude that on-chip RPA assay offers a rapid, high-throughput, and reliable tool for seafood authentication and potential mislabeling surveillance.

Photo by Patrick Boucher on Unsplash

This study (purchase required) reports development of a Loop-Mediated Isothermal Amplification (LAMP) assay to detect several common avian meat species as adulterants in raw and heat- and pressure-treated meat products. This is an on-site test, taking about 1 hour, with the results visualised by colour changes in the SYTO 24 nucleic acid marker dye.

Conserved regions of the glyceraldehyde-3-phosphate dehydrogenase (gapdh) gene were targeted to design a LAMP primer set specific to avian species. To assess the assay’s performance, six common avian species (chicken, turkey, goose, duck, ostrich, quail) and four non-avian species (sheep, cattle, goat, camel) were tested. DNA was extracted using a salt-based method, and the assay’s specificity and sensitivity were evaluated on raw, cooked, and autoclaved samples.

The authors report that the LAMP assay successfully detected chicken, turkey, goose, and duck DNA. They report detection limits of 110 femtograms chicken DNA In chicken–beef mixtures, 0.1 % chicken in raw and cooked samples and 1 % in autoclaved samples.

For the principle of LAMP, see FAN’s method explainer pages.

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This study (open access) aimed to identify the volatile compound components in chicken, beef, pork, and mixed (2-to-1 proportions) pork-containing satay, as well as determined the biomarker compounds for each type of satay meat.  The satay products were as commonly eaten in Indonesia, with cubes of meat barbequed on a skewer before adding the sauce.  Cooking in this manner gives the meat a distinct flavour, and the aim was to differentiate this by analysis of volatiles.

The volatile components in satay were extracted using the solid-phase microextraction (SPME) and analysed by gas chromatography-mass spectrometry (GC-MS). The data were processed using multivariate data analysis. 15 key volatile chemicals were measured.

Each type of satay meat exhibited good separation with the multivariate model. Beef and chicken satay were distinctly separated, whereas samples of pork and mixed pork-containing satay were positioned closely together.

The volatile compounds with the highest intensity in beef satay samples were nonanal, carbon disulfide, hexadecanal, and benzaldehyde. Chicken satay samples showed the highest levels of benzaldehyde, nonanal, hexadecanal, and hexadecane among the volatile compounds. In pork satay, the highest volatile compounds were cyclohexanol, 5-methyl-2-(1-methylethyl)-(1.alpha.,2.beta.,5.alpha.), hexanal, nonanal, benzaldehyde, and hexadecanal. Each type of satay meat was effectively separated, and mixed meat satay was positioned close to the pork satay group. The compounds identified as markers in beef satay were hexadecanal, nonanoic acid, ethylbenzene, pentadecanal, and heptadecanal. Chicken satay marker components included benzaldehyde; 2,3,5-trimethyl-6-ethylpyrazine; 2-nonenal, (E)-; linalool; 2-methylbutanal; and 3-methylbutanal. The marker components for pork satay and its mixtures were hexanal; thiophene, 2-methyl-; cyclodecene, (E)-; 2-methyl-2-butenal; and cyclodecene, (Z)-. These marker compounds present in each meat were highly correlated in the separation of satay samples.

The authors conclude that SPME-GC-MS successfully differentiated the satay meats and determined the compounds contributing most strongly to the separation.

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In this study (open access) researchers developed and piloted a single in-line sensor to classify yoghurt as either sheep, goat or milk origin and simultaneously check viscosity and pH Quality Attribute Specifications.  Their goal is a rapid in-line sensor that incorporates automated decision making, for routine use in the dairy industry.

Their reference dataset was sourced directly from two reputable Spanish companies and included both pasteurised and UHT yoghurts.

They found that the animal origin of milk could be predicted by building models based on the spectral data between 400 and 600 nm whilst viscosity and pH could be predicted by building models based on the spectral data between 800 and 1800 nm. To identify the animal origin of milk, they used Partial Least Squares-Discriminant Analysis (PLS-DA), achieving 100 % accuracy (95 % confidence interval). The model used to predict pH and viscosity was built with Partial Least Squares Regression (PLSR). The predictive power was generally very good (MSE=0.04–0.06; R²=0.94–0.96; MAE=0.16–0.17).

They conclude that their study demonstrates that the proposed spectroscopic method offers a more efficient approach for the simultaneous prediction of pH, viscosity, and milk origin in yogurt compared to existing methods, that require separate and slower analyses. Further work still needs to be carried out to optimize the model and achieve real-time monitoring that enables automated decision-making.

[picture – from the publication]

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.

Authentication of mushroom commodities often relies on visual identification, including microscopy. The methods usually involve physical observation with high subjectivity, which may lead to mushroom-product fraud and mislabelling.

This review (purchase required) covers molecular methods and “chemical” methods coupled with chemometrics and/or artificial intelligence. These include DNA barcoding, which is an identification strategy based on the DNA sequence of the mushroom sample, specifically the internal transcribed spacer (ITS) region. The review discusses the advancements in the usage of both DNA barcoding and chemometrics-coupled methods in the authentication of mushrooms and their derivative products; and how these can solve some major hurdles relating to mushroom products.

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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.

Shrimp surimi-based products (SSPs) are composed of minced shrimp meat and are highly susceptible to fraudulent substitution by cheaper fish surimi.

This study (open access) employed a double-gene metabarcoding approach to authenticate SSPs sold in bulk (business-to-business) on Chinese e-commerce platforms. 16S rRNA and 12S rRNA genes were amplified and sequenced from 24 SSPs. Mislabeling was evaluated based on the correspondence between the ingredients (only those of animal origin) reported on the products’ labels and the molecular results.

The authors found that 21 of the 24 products were mislabeled. The replacement of Penaeus vannamei with other shrimp species was particularly noteworthy. In some samples the primary species detected in terms of sequence abundance were not shrimp but fish, pork, chicken, and cephalopods. The 12S rRNA sequencing results revealed that fish species like Gadus chalcogrammus, Evynnis tumifrons, and Priacanthus arenatus were added to some SSPs in significant proportions, with certain products relying on fish priced from “Low” to “High” levels to substitute higher-cost shrimp. Notably, many fish species in SSPs were highly vulnerable to fishing, raising sustainability concerns.

The authors conclude that the high mislabeling rate, as well as the detection of endangered fish species (Pangasianodon hypophthalmus), underscores significant quality control and supply chain integrity issues.

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This paper (purchase required) reports a method to differentiate pork gelatin from beef gelatin (down to 0.01% cross-contamination levels) based on the LC-MSMS analysis of 13 peptide marker ions (8 for bovine, 5 for porcine).  The authors report that their method was validated at three concentration levels and accurately identified the gelatin species in pharmaceutical capsules and gels.

LC-MSMS analysis of peptides provides an alternative approach to DNA testing, which has known difficulties in application to highly processed products like gelatin due to the low amount of viable DNA or distinctive fragments.  LC-MSMS is the approach described in a recent Defra research report which is referenced on the FAN research pages (scroll down table to FA0177).

This study (open access) investigated species substitution, mislabeling, and the sustainability of seafood products in the seafood markets of South China. 478 samples were purchased from retail markets in 11 cities across three provinces (Guangxi, Guangdong, and Hainan) between May 2021 and December 2023. Cytochrome c oxidase subunit I (COI) gene amplification was used to identify 156 fish species across 105 genera and 60 families. The researchers have published the correlation between genetic and taxonomical details.

The researchers used a combination of morphological and DNA barcoding methods to produce an atlas guide for these 156 economically important fish species.

Molecular identification revealed that 9.6 % (15/156) of fish species were mislabelled, with commercial fraud detected in three processed species: Hilsa kelee, Chelidonichthys kumu, and Argyrosomus japonicus. Some substitutions may have been unintentional.  3.8 % (6/156) of species identified were classified as threatened by the International Union for Conservation of Nature. The study also uncovered an example of illicit cross-border sales of fish products.

The authors conclude that their findings provide a technical reference for effective fish species identification and offer valuable insights into seafood market monitoring.

Photo by Dan Gold on Unsplash

Meat species identification has always been a challenge in highly processed foods, such as gelatines and stocks.

One approach is to measure proteins and protein patterns using mass spectrometry (MS).  A previous research project, under the UK Department of Environment, Food and Rural Affairs (Defra) Food Authenticity Programme, developed and in-house validated a method using proteomics.

That work has now been built upon by another 3 Defra projects to streamline the method to look for specific markers, in a format that can be used routinely by testing laboratories, and to fully validate the routine method including by interlaboratory trial.

All four research reports are now signposted on FAN’s Research pages.  Scroll through the table to find the appropriate report reference number:

• FA0166 – the original 2019 project – “Development, optimisation and validation of a non-targeted proteomics method for meat species identification”
• FA0165 – “Liquid chromatography targeted mass spectrometry method to determine the animal origin of gelatine - transfer to a high throughput, low cost platform with single lab evaluation”
• FA0177 – “Gelatine species determination, completion of method validation and determination of a quantitative method”
• FA0187 – “Interlaboratory trial of a mass spectrometry method for meat species determination”

This paper (open access) reports a survey of 62 retail samples of processed whitefish products from British, Italian and Albanian retailers (mainly high-street supermarkets).  24 samples, spanning all regions, were reported as mislabelled using the criteria below.

The researchers used Next Generation Sequencing following DNA extraction using commercial kits.  Full details of the primers are given in the paper.  They prepared in-house positive and negative controls by blending various proportions of white fish species (from whole, identifiable, fillets) that are not used in commercial fish product manufacturing into mixtures of “authentic” species.

Since commercial designations of seafood species vary greatly both across and within countries, the researchers compared the ingredients provided for each product to the official list of commercial designation of the country where the product was purchased.. If a common name was declared on the label, the relevant species name was obtained searching FishBase , while if a scientific name was provided, it was contrasted directly with the molecular results.

Using matches and mismatches between label information and DNA-based identification, the researchers classified the examined products into the following categories: (i) “green” (correctly labelled product): when the proportion of reads of the declared species was at least twice as large as the second most abundant species and constitutes the majority of the bulk; (ii) “amber” (misleading product): when the proportion of the declared species was higher than any other species, but not necessarily amounting to the majority of the bulk; (iii) “red” (mislabelled product): when the declared species was either absent or not the most abundant in the mix; (iv) “grey” (undetermined product): when the declared species couldn’t be genetically identified with certainty.

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.