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This study (open access) builds on a previously-published proof of concept.  The authors are working towards producing a hand-held multi-mode scanner (combining fluorescence, visible, NIR, and short-wave IR spectroscopy) to support species verification of white fish fillets in business-to-business supply (currently reliant, largely, on visual recognition by experienced traders).

The explain that one of the key challenges in using machine learning for fish species identification is managing the large number of classes, as the variety of fish species is extensive. In their previous research, they introduced a novel multi-mode, highly multi-class machine learning framework based on a hierarchy of dispute models. This approach involved training a global model, and then recognizing groups of classes that have feature subspaces too similar for effective single-stage classification. By partitioning the overall space into smaller, distinct subspaces, they trained specialized models that are more tailored to these specific subsets of the dataset. In practice, the global model initially classified a sample to determine the appropriate subspace, while the dispute model then identified the precise species within that subspace.

The objective of this latest study was to apply this approach data acquired with the multi-mode handheld spectroscopy device. Tissue spectra were acquired at 25 positions on 68 fillets from 11 species, in both frozen and thawed states.

They report that feature-level fusion across the four spectroscopy modes enabled higher classification accuracy than any single mode alone. A global machine-learning model classified all species with 85 ± 2.8 %, while specialized dispute models for commonly misclassified species improved performance to 90 % ± 6.1 %. Individual models for thawed and frozen fillets achieved 90 ± 6.0 % and 90 ± 5.4 %, respectively, with dispute models in the thawed dataset increasing accuracy to 93 ± 4.3 %.

They conclude that their results demonstrate that portable multi-mode spectroscopy, combined with machine learning, can provide a fast, non-destructive and reliable tool for on-site fish species identification.

N-glycans are a class of biological compound that are chemically bound to proteins.  They are generally stable to food processing and heating.

In this paper (open access) the authors investigated how N-glycans varied amongst three different fish species; red snapper, barramundi (Asian Sea Bass) and the potentially cheaper adulterant, tilapia.  They measured N-glycan profiles using liquid chromatography with ion mobility and mass spectrometry (LC-IM-MS).  They identified four N-glycan structures containing different degrees of O-acetylated sialic acids (O-Ac-Sias) as species-specific markers and found clear clustering based on their percentage abundance.  This enabled a multi-class species classification model.  They found that this clustering and classification model remained valid even after the fish had been cooked and processed.

They conclude that this approach could complement DNA testing when looking at heavily processed or manufactured food.

Around 80% of the seafood consumed in the UK is imported. Much of it comes from Norway, Iceland, Vietnam, and more countries.

In the latest issue of Food Science and Technology, Ivan Bartolo explores the UK’s reliance on imported seafood, driven by consumer preferences, global supply chains, and the demands of fish processing factories.

The article also explains how food safety is maintained, how the country determines the origin of seafood, and the environmental and resilience challenges associated with these imports.

Access full article: https://doi.org/10.1093/foodst/vwaf044

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).

Photo by Marko Markovic on Unsplash

In this study (open access) the researchers proposes using a MALDI-ToF and LC-Q-ToF dual approach, following trypsin digestion, as a method to verify fish species.  Trypsin digestion breaks the proteins down into peptides, and they used peptide fingerprints to identify peptides that were unique markers for specific species. The advantage of their approach over DNA methods, and in comparison to MALDI-ToF-MS analysis of undigested proteins, is that it can be applied to complex and heat-processed samples.

The study aimed to differentiate six fish species—carp, mackerel, pike, pollock, salmon and trout. Matrix-assisted laser desorption/ionization–time ff flight mass spectrometry (MALDI-TOF MS) was employed to identify characteristic species-specific m/z values to differentiate raw and cooked fish meat. Additionally, liquid chromatography–electrospray ionization–quadrupole–time tf flight (LC-ESI-Q-TOF) was used to determine specific amino acid sequences in carp and salmon, selected as model species.

Two or more distinct species-specific m/z markers were identified for all six fish species, enabling their differentiation in both raw and processed form. A slightly larger list of distinct markers were found for cooked, compared to raw, fish.  In carp and salmon, hundreds of peptide sequences were detected, leading to the identification of a panel of peptide markers that determine both the fish species and the type of meat processing. The results confirm that mass spectrometry-based proteomic approaches can serve as effective tools for the authentication of fish meat.

The authors conclude that it is possible to use two complementary mass spectrometry techniques for reliable and rapid authentication of fish species. By focusing on peptide-level markers and leveraging accessible tools, they believe that the approach offers a cost-effective and innovative alternative for fish meat authentication.

This study (purchase required) is unusual in that it sought to investigate the seasonality of fraud over a 12-month period.

Samples were collected from three Peruvian coastal cities—Lima, Chiclayo, and Piura. A total of 1189 samples were collected from 76 retail points, including restaurants, supermarkets, and municipal markets. DNA barcode sequencing was used for species identification, revealing a 67.5 % substitution rate. Restaurants exhibited the highest substitution rate (73.8 %), followed by municipal markets (71.1 %) and supermarkets (27.9 %). Fraud was identified in 89.7 % of substitution cases, often involving high-demand or threatened species, such as hammerhead sharks Sphyrna zygaena and Atlantic eel Anguilla anguilla.

The authors report that seasonal patterns were observed, with certain species like dolphinfish Coryphaena hippurus and searobin Prionotus stephanophrys used more frequently at certain times of year.

Photo by Patrick Browne on Unsplash - for illustration, there is no suggestion that this dish is fraudulent

This publication (open access) describes the launch of FISH-FIT.  FISH-FIT is a biobank of seafood species samples which are linked to an authentic database of morphology, genetic information, and other physical characteristics. It also contains a library of PCR analytical methods.   It was developed under an EU-funded project and free access is currently only available to EU regulatory bodies, although wider access is planned.  The databank is hosted by the Max Ruber Institute.

FISH-FIT has been added to FAN’s index of authenticity reference databases, a useful search tool for existing databanks or commercial testing services..

(image from the paper)

This review (open access, pre-publication) collates published surveys of seafood mislabelling in Asia (the time period reviewed is not stated).  The authors list results along with the testing methodologies used, listing separate results for China, India, South Korea, Indonesia, Malaysia, Philippines, Singapore and Taiwan.  Some surveys, particularly of specialist fish powders or premium smoked fish products, reported mislabelling rates of 70 or 80%.  More typical mislabelling rates for fillets sold as a single species were around 7 or 8%.

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.

Photo by Fernando Andrade on Unsplash

The  aim of this proof-of-principle study (open access) was to design a universal DNA microarray (“DNA Chip”) to distinguish all edible fish species by comparing hybridization signal patterns from samples with patterns obtained from reference specimens.

The researchers designed a universal set of 96 DNA probes that cover all fish species of food interest.  These were narrowed down by virtual modelling experiments from a long-list of 28,000 candidates which they had generated experimentally. They also included 4 control probes (sequences not present in edible fish).  All probes were based on sequences from either 16S ribosomal RNA or cytochrome b.

DNA was isolated with either a CTAB method or with commercial DNA extraction kits. The gene markers cytb (approx. 464 bp) and 16S rDNA (approx. 600 bp) and an additional pUC57 vector DNA region (542 bp) were amplified in triplex PCRs. The DNA probes were spotted contactless using piezoelectric dispensing technology as 19 × 19 arrays. For hybridization of the generated PCR amplicons on the prepared microarrays the INTER-ARRAY Hybridization Kit was used according to manufacturer's specifications. The arrays were measured directly after staining and then processed using the INTER-VISION GENOTYPING 1.2.0 software.

The authors tested 86 fish fillets sourced from verified suppliers and were able to correctly identify all species by hierarchical clustering analysis of the results.  The entire process takes a few hours.  They conclude that the method is ready for further validation and ruggedness testing. More replicates and species should be analyzed to confirm current results. Likewise, the robustness of the DNA array should be determined, e. g. by using different thermocycler or users and laboratories.

Graphical abstract from the paper

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

The Indian Council of Agricultural Research Central Institute of Fisheries Technology (ICAR-CIFT) in Kochi has just hosted a national workshop on Food Authenticity and Traceability using Omics Techniques.

ICAR-CIFT has also signed a Memorandum of Understanding with Waters (a large laboratory instrument supplier) to act as a showcase laboratory and application development centre for authenticity testing.   The announcement is expected to boost research and builds on the regional hub in and around Kochi of laboratories with expertise in fish analysis.

The ICAR-CIFT announcement is here.

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.

This artefactual field experiment explores consumers’ willingness-to-pay (WTP) price premiums for fish products to avoid the risk and uncertainty of purchasing inauthentic produce.

The influence of subjective probabilistic beliefs, risk and ambiguity preferences is investigated. Participants’ WTP is elicited using experimental auctions, while behavioural factors are elicited using incentivised and incentive-compatible methods: the quadratic scoring rule and multiple price lists.

Results show that consumers are willing to pay a premium to avoid food fraud and purchase an authentic fish product. This premium is higher under uncertainty than risk, likely driven by ambiguity preferences which affect consumers’ purchasing under uncertainty.

Read full article.

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.

In a move that customers have labelled very fishy, the Chinese government has ruled that rainbow trout can now be labelled and sold as salmon.

The seemingly bizarre move comes after complaints earlier this year that rainbow trout was being mislabelled.

In May, media reported that much of what was sold as salmon in China was actually rainbow trout, to widespread consternation from fish-buyers.

But instead of banning vendors from deceiving their customers, the China Aquatic Products Processing and Marketing Alliance (CAPPMA), which falls under the Chinese ministry of agriculture, has ruled that all salmonidae fish can now be sold under the umbrella name of “salmon”, reports the Global Times.

Rainbow trout and salmon are both salmonidae fish and look quite similar when filleted. However, salmon live in salt water and rainbow trout live in fresh water.

Read the full article.