Traceability of organic fish – Authenticating the production origin of salmonids by chemical and isotopic analyses

Enhancing seafood traceability: tracking the origin of seabass and seabream from the tuscan coast area by the analysis of the gill bacterial communities

BACKGROUND

The seafood consumption and trade have increased over the years, and along its expected expansion pose major challenges to the seafood industry and government institutions. In particular, the global trade in fish products and the consequent consumption are linked to reliable authentication, necessary to guarantee lawful trade and healthy consumption. Alterations or errors in this process can lead to commercial fraud and/or health threats. Consequently, the development of new investigative tools became crucial in ensuring unwanted scenarios. Here we used NGS techniques through targeted metagenomics approach on the V3-V4 region of the 16S rRNA genes to characterize the gill bacterial communities in wild-caught seabream (Sparus aurata) and seabass (Dicentrarchus labrax) within different fisheries areas of the "Costa degli Etruschi'' area in the Tuscan coast. Our challenge involved the possibility of discriminating between the microbiota of both fish species collected from three different fishing sites very close to each other (all within 100 km) in important areas from a commercial and tourist point of view.

RESULTS

Our results showed a significant difference in the assembly of gill bacterial communities in terms of diversity (alpha and beta diversity) of both seabass and seabream in accordance with the three fishing areas. These differences were represented by a unique site -related bacterial signature, more evident in seabream compared to the seabass. Accordingly, the core membership of seabream specimens within the three different sites was minimal compared to the seabass which showed a greater number of sequence variants shared among the different fishing sites. Therefore, the LRT analysis highlighted the possibility of obtaining specific fish bacterial signatures associated with each site; it is noteworthy that specific taxa showed a unique association with the fishing site regardless of the fish species. This study demonstrates the effectiveness of target-metagenomic sequencing of gills in discriminating bacterial signatures of specimens collected from fishing areas located at a limited distance to each other.

CONCLUSIONS

This study provides new information relating the structure of the gill microbiota of seabass and seabream in a fishing area with a crucial commercial and tourist interest, namely "Costa degli Etruschi". This study demonstrated that microbiome-based approaches can represent an important tool for validating the seafood origins with a central applicative perspective in the seafood traceability system.

Differentiating wild from captive animals: an isotopic approach

Background

Wildlife farming can be an important but complex tool for conservation. To achieve conservation benefits, wildlife farming should meet a variety of criteria, including traceability conditions to identify the animals' origin. The traditional techniques for discriminating between wild and captive animals may be insufficient to prevent doubts or misdeclaration, especially when labels are not expected or mandatory. There is a pressing need to develop more accurate techniques to discriminate between wild and captive animals and their products. Stable isotope analysis has been used to identify animal provenance, and some studies have successfully demonstrated its potential to differentiate wild from captive animals. In this literature review, we examined an extensive collection of publications to develop an overall picture of the application of stable isotopes to distinguish between wild and captive animals focusing on evaluating the patterns and potential of this tool.

Survey methodology

We searched peer-reviewed publications in the Web of Science database and the references list from the main studies on the subject. We selected and analyzed 47 studies that used δ13C, δ15N, δ2H, δ18O, and δ34S in tissues from fish, amphibians, reptiles, birds, and mammals. We built a database from the isotope ratios and metadata extracted from the publications.

Results

Studies have been using stable isotopes in wild and captive animals worldwide, with a particular concentration in Europe, covering all main vertebrate groups. A total of 80.8% of the studies combined stable isotopes of carbon and nitrogen, and 88.2% used at least one of those elements. Fish is the most studied group, while amphibians are the least. Muscle and inert organic structures were the most analyzed tissues (46.81% and 42.55%). δ13C and δ15N standard deviation and range were significantly higher in the wild than in captive animals, suggesting a more variable diet in the first group. δ13C tended to be higher in wild fishes and in captive mammals, birds, reptiles, and amphibians. δ15N was higher in the wild terrestrial animals when controlling for diet. Only 5.7% of the studies failed to differentiate wild and captive animals using stable isotopes.

Conclusions

This review reveals that SIA can help distinguish between wild and captive in different vertebrate groups, rearing conditions, and methodological designs. Some aspects should be carefully considered to use the methodology properly, such as the wild and captivity conditions, the tissue analyzed, and how homogeneous the samples are. Despite the increased use of SIA to distinguish wild from captive animals, some gaps remain since some taxonomic groups (e.g., amphibians), countries (e.g., Africa), and isotopes (e.g., δ2H, δ18O, and δ34S) have been little studied.

Isotope Fingerprinting as a Backup for Modern Safety and Traceability Systems in the Animal-Derived Food Chain

In recent years, due to the globalization of food trade and certified agro-food products, the authenticity and traceability of food have received increasing attention. As a result, opportunities for fraudulent practices arise, highlighting the need to protect consumers from economic and health damages. In this regard, specific analytical techniques have been optimized and implemented to support the integrity of the food chain, such as those targeting different isotopes and their ratios. This review article explores the scientific progress of the last decade in the study of the isotopic identity card of food of animal origin, provides the reader with an overview of its application, and focuses on whether the combination of isotopes with other markers increases confidence and robustness in food authenticity testing. To this purpose, a total of 135 studies analyzing fish and seafood, meat, eggs, milk, and dairy products, and aiming to examine the relation between isotopic ratios and the geographical provenance, feeding regime, production method, and seasonality were reviewed. Current trends and major research achievements in the field were discussed and commented on in detail, pointing out advantages and drawbacks typically associated with this analytical approach and arguing future improvements and changes that need to be made to recognize it as a standard and validated method for fraud mitigation and safety control in the sector of food of animal origin.

Identification of Fish Species and Targeted Genetic Modifications Based on DNA Analysis: State of the Art

Food adulteration is one of the most serious problems regarding food safety and quality worldwide. Besides misleading consumers, it poses a considerable health risk associated with the potential non-labeled allergen content. Fish and fish products are one of the most expensive and widely traded commodities, which predisposes them to being adulterated. Among all fraud types, replacing high-quality or rare fish with a less valuable species predominates. Because fish differ in their allergen content, specifically the main one, parvalbumin, their replacement can endanger consumers. This underlines the need for reliable, robust control systems for fish species identification. Various methods may be used for the aforementioned purpose. DNA-based methods are favored due to the characteristics of the target molecule, DNA, which is heat resistant, and the fact that through its sequencing, several other traits, including the recognition of genetic modifications, can be determined. Thus, they are considered to be powerful tools for identifying cases of food fraud. In this review, the major DNA-based methods applicable for fish meat and product authentication and their commercial applications are discussed, the possibilities of detecting genetic modifications in fish are evaluated, and future trends are highlighted, emphasizing the need for comprehensive and regularly updated online database resources.

Stable Isotope Analysis for the Discrimination of the Geographical Origin of Greek Bottarga ‘Avgotaracho Messolongiou’: A Preliminary Research

Consumers are increasingly interested in the geographical origin of the foodstuff they consume as an important characteristic of food authenticity and quality. To assure the authenticity of the geographical origin, various methods have been proposed. Stable isotope analysis is a method that has been extensively used for products such as wine, oil, meat, while only a few studies have been conducted for the discrimination of seafood origin and especially for mullet roes or bottarga products. Analysis of the stable isotopes of C, N and S of Bottarga samples from four different origins were carried out. The values of δ¹⁵N (5.45‰) and δ³⁴S (4.66‰) for the Greek Bottarga Product named ‘Avgotaracho Messolongiou’, from Messolongi lagoon were lower than other areas while δ¹³C values were higher (−14.84‰). The first results show that the stable isotopes ratios of carbon, nitrogen and sulphur could be used to discriminate the Greek Protected Designations of Origin Bottarga product ‘Avgotaracho Messolongiou’ from other similar products.

Food traceability 4.0 as part of the fourth industrial revolution: key enabling technologies

Food Traceability 4.0 (FT 4.0) is about tracing foods in the era of the fourth industrial revolution (Industry 4.0) with techniques and technologies reflecting this new revolution. Interest in food traceability has gained momentum in response to, among others events, the outbreak of the COVID-19 pandemic, reinforcing the need for digital food traceability that prevents food fraud and provides reliable information about food. This review will briefly summarize the most common conventional methods available to determine food authenticity before highlighting examples of emerging techniques that can be used to combat food fraud and improve food traceability. A particular focus will be on the concept of FT 4.0 and the significant role of digital solutions and other relevant Industry 4.0 innovations in enhancing food traceability. Based on this review, a possible new research topic, namely FT 4.0, is encouraged to take advantage of the rapid digitalization and technological advances occurring in the era of Industry 4.0. The main FT 4.0 enablers are blockchain, the Internet of things, artificial intelligence, and big data. Digital technologies in the age of Industry 4.0 have significant potential to improve the way food is traced, decrease food waste and reduce vulnerability to fraud opening new opportunities to achieve smarter food traceability. Although most of these emerging technologies are still under development, it is anticipated that future research will overcome current limitations making large-scale applications possible.

Review: Quality and authentication of organic animal products in Europe

The 'organic' label guarantees a production process that avoids the use of synthetic fertilisers, pesticides and hormones and minimises the use of veterinary drugs; however, consumers are demanding guarantees regarding food quality. This article reviews the current state of knowledge on the quality of organic animal products, including the authentication of their organic origin. Quality has been considered as an integrative combination of six core attributes: commercial value, and nutritional, sensory, technological, convenience and safety attributes. The comparison of these attributes between organic and conventional animal products shows high heterogeneity due to variability in farming pratices in both organic and conventional systems. To overcome this, we pinpoint the farming practices underlying the differences observed. This enables light to be shed on the consequences of possible trajectories of organic farming, if specifications are relaxed or tightened up on commitments concerning farming practices that impact product quality. Two recent meta-analyses showed better nutritional attributes in organic milk and meat linked to their higher poly-unsaturated fatty acid (PUFA) content, particularly n-3 PUFAs. Regarding safety, we point to a lack of integrated studies quantifying the balance between positive and negative effects. Organic farming reduces the risk of drug residues and antibiotic resistance, but both outdoor rearing and a frequently longer rearing period increase the animals' exposition to environmental contaminants and the risk of their bioaccumulation in milk, eggs, meat and fish flesh. We highlight antagonisms between quality attributes for certain animal products (lamb, pork). In general, attributes are more variable for organic products, which can be explained by lower genetic selection (poultry), lower inputs and/or greater variability in farming conditions. However, the literature does not address the implications of this greater variability for the consumers' acceptability and the necessary adaptation of manufacturing processes. Further research is needed to document the impacts on human nutritional biomarkers and health. Methods used to authenticate organic origin are based on differences in animal diet composition between organic and conventional systems, but their reliability is hampered by the variability in farming practices.

Advances in Troubleshooting Fish and Seafood Authentication by Inorganic Elemental Composition

The demand for fish and seafood is growing worldwide. Meanwhile, problems related to the integrity and safety of the fishery sector are increasing, leading legislators, producers, and consumers to search for ways to effectively protect themselves from fraud and health hazards related to fish consumption. What is urgently required now is the availability of reliable, truthful, and reproducible methods assuring the correspondence between the real nature of the product and label declarations accompanying the same product during its market life. The evaluation of the inorganic composition of fish and seafood appears to be one of the most promising strategies to be exploited in the near future to assist routine and official monitoring operations along the supply chain. The present review article focuses on exploring the latest scientific achievements of using the multi-elemental composition of fish and seafood as an imprint of their authenticity and traceability, especially with regards to the geographical origin. The scientific literature of the last 10 years focusing on the analytical determination and statistical elaboration of elemental data (alone or in combination with methodologies targeting other compounds) to verify the identity of fishery products is summarized and discussed.

Chilean Salmon Sushi: Genetics Reveals Product Mislabeling and a Lack of Reliable Information at the Point of Sale

Species diagnosis is essential to assess the level of mislabeling or misnamed seafood products such as sushi. In Chile, sushi typically includes salmon as the main ingredient, but species used are rarely declared on the menu. In order to identify which species are included in the Chilean sushi market, we analyzed 84 individual sushi rolls sold as "salmon" from sushi outlets in ten cities across Chile. Using a polymerase chain reaction-restriction fragment length polymorphism protocol (PCR-RFLP), we identified mislabeled and misnamed products. Atlantic salmon was the most common salmonid fish used in sushi, followed by coho salmon, rainbow trout, and Chinook salmon. We found a total of 23% and 18% of the products were mislabeled and misnamed, respectively. In 64% of cases, the salesperson selling the product could not identify the species. We also identified the use of wild-captured Chinook salmon samples from a naturalized population. Our results provide a first indication regarding species composition in Chilean sushi, a quantification of mislabeling and the level of misinformation declared by sales people to consumers. Finally, considering that Chinook salmon likely originates from a non-licensed origin and that sushi is an uncooked product, proper identification in the food production chain may have important consequences for the health of consumers.

Machine Learning Approaches Applied to GC-FID Fatty Acid Profiles to Discriminate Wild from Farmed Salmon

In the last decade, there has been an increasing demand for wild-captured fish, which attains higher prices compared to farmed species, thus being prone to mislabeling practices. In this work, fatty acid composition coupled to advanced chemometrics was used to discriminate wild from farmed salmon. The lipids extracted from salmon muscles of different production methods and origins (26 wild from Canada, 25 farmed from Canada, 24 farmed from Chile and 25 farmed from Norway) were analyzed by gas chromatography with flame ionization detector (GC-FID). All the tested chemometric approaches, namely principal components analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE) and seven machine learning classifiers, namely k-nearest neighbors (kNN), decision tree, support vector machine (SVM), random forest, artificial neural networks (ANN), naïve Bayes and AdaBoost, allowed for differentiation between farmed and wild salmons using the 17 features obtained from chemical analysis. PCA did not allow clear distinguishing between salmon geographical origin since farmed samples from Canada and Chile overlapped. Nevertheless, using the 17 features in the models, six out of the seven tested machine learning classifiers allowed a classification accuracy of ≥99%, with ANN, naïve Bayes, random forest, SVM and kNN presenting 100% accuracy on the test dataset. The classification models were also assayed using only the best features selected by a reduction algorithm and the best input features mapped by t-SNE. The classifier kNN provided the best discrimination results because it correctly classified all samples according to production method and origin, ultimately using only the three most important features (16:0, 18:2n6c and 20:3n3 + 20:4n6). In general, the classifiers presented good generalization with the herein proposed approach being simple and presenting the advantage of requiring only common equipment existing in most labs.

Differentiating wild, lake-farmed and pond-farmed carp using stable isotope and multi-element analysis of fish scales with chemometrics

Stable carbon (δ¹³C) and nitrogen (δ¹⁵N) isotope ratios and multi-element signatures of pooled fish scales were used to differentiate wild, lake-farmed and pond-farmed carp from Dongting Lake, China. Fish scales were found to be important archives for the dietary history and trophic level of wild and farmed fish, indicating their food sources. δ¹³C and δ¹⁵N values of pond-farmed carp scales were comparatively enriched to wild and lake-farmed carp due to their animal protein-derived feeds. Multi-element compositions of fish scales also showed significant differences between wild and farmed fish. A partial least squares discriminant analysis (PLS-DA) model correctly discriminated the three carp groups. Discrimination accuracies of wild, lake-farmed and pond-farmed carp were 100%, 95%, and 100% for the training set, and 100% for the testing set. This strategy provides a promising non-lethal alternative method to combat mislabeling of freshwater carp from different farming methods.

Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years

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. It is the aim of the present manuscript to review 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 will also be discussed.

Differentiating salmonid migratory ecotypes through stable isotope analysis of collagen: Archaeological and ecological applications

The ability to distinguish between different migratory behaviours (e.g., anadromy and potamodromy) in fish can provide important insights into the ecology, evolution, and conservation of many aquatic species. We present a simple stable carbon isotope (δ13C) approach for distinguishing between sockeye (anadromous ocean migrants) and kokanee (potamodromous freshwater residents), two migratory ecotypes of Oncorhynchus nerka (Salmonidae) that is applicable throughout most of their range across coastal regions of the North Pacific Ocean. Analyses of kokanee (n = 239) and sockeye (n = 417) from 87 sites spanning the North Pacific (Russia to California) show that anadromous and potamodromous ecotypes are broadly distinguishable on the basis of the δ13C values of their scale and bone collagen. We present three case studies demonstrating how this approach can address questions in archaeology, archival, and conservation research. Relative to conventional methods for determining migratory status, which typically apply chemical analyses to otoliths or involve genetic analyses of tissues, the δ13C approach outlined here has the benefit of being non-lethal (when applied to scales), cost-effective, widely available commercially, and should be much more broadly accessible for addressing archaeological questions since the recovery of otoliths at archaeological sites is rare.

Geographical origin traceability and species identification of three scallops (Patinopecten yessoensis, Chlamys farreri, and Argopecten irradians) using stable isotope analysis

Traceability and authenticity is crucial to the food safety of scallop. The present study investigated the possibility of using stable isotope analysis to identify the origins and species of scallops (Patinopecten yessoensis, Chlamys farreri, and Argopecten irradians) in the coastal areas of China. The δ¹³C and δ¹⁵N values of a total of 575 samples from seven sites around China were determined and additional 150 samples were tested by fisher linear discrimination analysis (LDA) to estimate the accuracy of origin identification and species prediction. The results show that the stable C and N isotope composition differed significantly depending on the origin, season and species of scallops. Meanwhile, the LDA shows that 92% of the samples were correctly classified for origin prediction, and an accuracy of 98.3% was obtained for species prediction. This study reveals that stable isotope ratio is an effective technique to trace the geographical origin and identify the species of scallops.

Know your fish: A novel compound-specific isotope approach for tracing wild and farmed salmon

The rapid expansion of the aquaculture industry with carnivorous fish such as salmon has been accompanied by an equally rapid development in alternative feed ingredients. This has outpaced the ability of prevailing authentication method to trace the diet and origins of salmon products at the retail end. To close this gap, we developed a new profiling tool based on amino acid δ¹³C fingerprints. With this tool, we discriminated with high-accuracy among wild-caught, organically, and conventionally farmed salmon groups, as well as salmon fed alternative diets such as insects and macroalgae. Substitution of fishmeal with macroalgae was detected at 5% difference level. The δ¹³C fingerprints of essential amino acids appear particularly well suited for tracing protein sources, and the non-essentials for tracing lipid origins (terrestrial vs. aquatic). In an industry constantly developing new feed proteins and functional additives, our method is a promising tool for tracing salmon and other seafood products.

Determination of the Geographical Origin of All Commercial Hake Species by Stable Isotope Ratio (SIR) Analysis

The determination of the geographical origin of food products is relevant to comply with the legal regulations of traceability, to avoid food fraud, and to guarantee food quality and safety to the consumers. For these reasons, stable isotope ratio (SIR) analysis using an isotope ratio mass spectrometry (IRMS) instrument is one of the most useful techniques for evaluating food traceability and authenticity. The present study was aimed to determine, for the first time, the geographical origin for all commercial fish species belonging to the Merlucciidae family using SIR analysis of carbon (δ¹³C) and nitrogen (δ¹⁵N). The specific results enabled their clear classification according to the FAO (Food and Agriculture Organization of the United Nations) fishing areas, latitude, and geographical origin in the following six different clusters: European, North African, South African, North American, South American, and Australian hake species.