Check Your Shopping Cart: DNA Barcoding and Mini-Barcoding for Food Authentication
by
, , and
Tommaso Gorini
1,
Valerio Mezzasalma
1,
Marta Deligia
2,
Fabrizio De Mattia
1,
Luca Campone
3,
Massimo Labra
3 and
Jessica Frigerio
3,* 1
FEM2-Ambiente, Piazza della Scienza 2, 20126 Milano, Italy
2
Department of Scienze Agrarie, Forestali e Alimentari, University of Turin, Via Verdi 8, 10124 Torino, Italy
3
Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza 2, 20126 Milano, Italy
*
Author to whom correspondence should be addressed.
Foods 2023, 12(12), 2392; https://doi.org/10.3390/foods12122392
Submission received: 16 May 2023
/
Revised: 7 June 2023
/
Accepted: 14 June 2023
/
Published: 16 June 2023
(This article belongs to the Section Food Quality and Safety)
Abstract
:The molecular approach of DNA barcoding for the characterization and traceability of food products has come into common use in many European countries. However, it is important to address and solve technical and scientific issues such as the efficiency of the barcode sequences and DNA extraction methods to be able to analyze all the products that the food sector offers. The goal of this study is to collect the most defrauded and common food products and identify better workflows for species identification. A total of 212 specimens were collected in collaboration with 38 companies belonging to 5 different fields: seafood, botanicals, agrifood, spices, and probiotics. For all the typologies of specimens, the most suitable workflow was defined, and three species-specific primer pairs for fish were also designed. Results showed that 21.2% of the analyzed products were defrauded. A total of 88.2% of specimens were correctly identified by DNA barcoding analysis. Botanicals (28.8%) have the highest number of non-conformances, followed by spices (28.5%), agrifood (23.5%), seafood (11.4%), and probiotics (7.7%). DNA barcoding and mini-barcoding are confirmed as fast and reliable methods for ensuring quality and safety in the food field.
1. Introduction
The complexity of the food supply network, including disruption due to COVID-19 and climate change, can make food products more vulnerable to fraud and substitution. It is difficult to quantify the impact of fraud on the whole food field because not all fraud is detected. However, food safety experts interviewed by Spielman estimated the impact of fraud on the food industry to be in excess of USD 50 billion annually [1]. Food fraud can occur anywhere in the food supply chain, from the seed supply to food packaging. Mislabelling (20.7%), artificial enhancement (17.2%), and substitution (16.4%) were the most commonly reported types of fraud [2]. Mislabelling has been frequently reported in the literature: up to 57% in processed meat products [3,4], up to 80% in fish filets [5,6], and up to 80% in dairy products [7]. Concerning the herbal supplements field, a global survey showed that 27% of herbal products commercialized in the global marketplace are adulterated. The most defrauded regions are Australia (79% mislabelled products) followed by South America (67% mislabelled products) [8]. Undeclared species substitution in food products might also represent an important health threat to allergic consumers because of the introduction of food allergens, such as different kinds of nuts and mollusks [9] or poisonous plants [10]. Even though it is a current problem, agribusiness has not paid sufficient attention to this issue. Most fraud is harmless, and this leads to a lack of attention. Nevertheless, the consumers have a large interest in the quality of food. McCallum and colleagues investigate consumers’ willingness to pay for premium products to reduce risk and uncertainty related to food fraud, showing that consumers are willing to pay for premium products to avoid food fraud and purchase an authentic product [11]. In this regard, blockchain has emerged as a promising technology that allows users to trace food products and eliminate or reduce harmful food fraud.
Treiblmaier and Garaus investigate how the use of blockchain to trace food products impacts consumers’ perception of product quality, finding that blockchain labels help to strengthen consumers’ perceived quality of food products which, in turn, increases their purchase intention [12]. Introducing DNA analysis into supply chain control could increase consumers’ confidence and consequently the budget allocated for food shopping. DNA barcoding has been frequently used in the literature for food authentication and supply chain control [13,14,15].
The application of DNA barcoding in food authentication is rooted in the concept of using short and standardized DNA sequences to differentiate between species. The technique targets specific regions of the genome, such as the mitochondrial DNA (mtDNA) or chloroplast DNA (cpDNA), which exhibit sufficient variability among species while maintaining conserved regions within the same species [16,17]. By comparing the barcode sequences obtained from unknown samples with well-curated reference databases, such as ncbi (https://www.ncbi.nlm.nih.gov/nucleotide/ accessed on 1 May 2023) and BOLD (https://www.boldsystems.org/ accessed on 1 May 2023), DNA barcoding allows for the identification of species present in food products, thereby enabling the detection of fraudulent practices.
One of the key advantages of DNA barcoding is its ability to detect adulteration and substitution in complex food matrices [18]. The technique can differentiate between closely related species or detect the presence of non-declared ingredients, even in processed or highly fragmented products. For instance, in cases where premium and expensive seafood species are substituted with cheaper alternatives, DNA barcoding can expose such fraudulent activities by identifying the true species present in the sample [19]. Similarly, it can detect the presence of allergenics that may pose health risks to consumers. Furthermore, DNA barcoding can aid in the identification of geographical origins or specific cultivars, providing valuable information regarding product quality, cultural heritage, and compliance with geographical indication regulations [20].
The use of DNA barcoding in combating food fraud has gained significant attention worldwide. Governments, regulatory agencies, and industry stakeholders recognize its potential to ensure food authenticity, protect consumer rights, and maintain market integrity. In recent years, various countries and international organizations have established initiatives and regulations to promote the adoption of DNA barcoding as a standard practice in food authentication. These include The EU Agri-Food Fraud Network (FFN), the United States Food and Drug Administration’s (FDA) GenomeTrakr program, and the International Organization for Standardization’s (ISO) guidelines on DNA-based methods for food authenticity testing.
Despite its numerous benefits, DNA barcoding is not without limitations. Challenges related to sample preparation, DNA extraction, database completeness, and the availability of suitable reference materials need to be addressed for wider adoption and successful implementation. Furthermore, ongoing advancements in DNA sequencing technologies, bioinformatics tools, and reference databases are vital to enhance the accuracy, efficiency, and reliability of DNA barcoding in food fraud detection.
This study aimed to identify several workflows of DNA barcoding for supply chain control in different food fields. A total of 38 companies, operating in 5 different fields (seafood, botanicals, agrifood, spices, and probiotics) supplied some of their high-selling products for a total of 212 specimens. Among these samples we can find fish filets, herbal teas, truffles, caviar, canned fish, processed products, powders, plant extracts, food supplements, flours, etc., a mix of products that can be considered representative of a supermarket shopping cart. The technical goals of the study are to (i) define the most suitable extraction methods for food matrices, (ii) identify the most suitable barcode region useful for different types of products (i.e., fresh, processed, etc.) and designed primer pairs when necessary, and (iii) estimate the ability of DNA barcoding tools to assess fraud in high-selling products.
2. Materials and Methods
2.1. Specimen Collection
The specimen collection was based on some defined criteria: (i) the most counterfeit species according to the literature were collected, (ii) sampling of the same species belonging to different companies was preferred, and (iii) when possible, raw/fresh, intermediate, and final products were collected. A total of 46 companies operating in the food field were contacted to join this study. The companies were chosen considering the food field operating (seafood, agrifood, spices, botanicals, and probiotic) with the aim to cover the most defrauded fields. A total of 38 companies agreed to participate in the project and a total of 212 specimens were collected (Table A1). In this study, we analyzed different typologies of products, from fresh (fish filets) to highly processed products (food supplements).
2.2. DNA Extraction
Considering the wide typology of specimens tested in this study, different commercial kits and extraction methods were chosen based on the literature [21,22,23,24]. For seafood specimens (fresh and intermediate specimens), Tissue Genomic DNA Extraction (Fisher Molecular Biology, Rome, Italy) (TGF) was selected and for more difficult products, such as canned fish and products preserved in oil and brine; the ReliaPrep™ gDNA Tissue MiniPrep System (Promega, Milan, Italy) (RPP) was tested/used with a modification to the protocol. The products preserved in brine were washed three times with a physiological solution (NaCl 0.7%), mixing overnight at room temperature. Canned specimens were pretreated in order to clean the tissue from the conservation liquid, such as oil (vegetable and olive); briefly, oil and lipids were removed by soaking in chloroform/methanol/water (1:2:0.8) and mixing overnight at room temperature [24].
For agrifood products, spices, and botanicals, a DNeasy Plant Kit (QIAGEN, Milan, Italy) (DPQ) was used following the instructions. For more complex samples belonging to these fields, such as phytoextract, the CTAB method was also applied [25]. The CTAB method allows us to start from a higher amount of material (1 g) and to harvest all the DNA in the solution.
Finally, for probiotic specimens, QIAamp DNA Microbiome Kit (QIAGEN) (QAQ) was used. In Table A1 are shown all the extraction methods used for all specimens. Purified gDNA was checked for concentration and purity by using a Qubit 2 Fluorometer and Qubit dsDNA HS Assay Kit (Invitrogen, Carlsbad, CA, USA).
2.3. Barcode Region Selection
A universal set of DNA barcoding markers for each product was tested. Specifically, different primer pairs were selected for animals, plants, fungi, and bacteria.
2.3.1. Animal DNA Barcoding
The amplification efficiency of the barcode region is associated with the primer pairs. A primer pair specific for a universal barcode region should be versatile across a wide range of animal species and have high affinity to DNA templates. Nevertheless, sometimes the universal primers are not applicable for certain taxa or specimens and it is necessary to redesign primers, as for some specimens in this study [26]. The barcode regions chosen for animal identifications were the mitochondrial markers COI (Cytochrome c oxidase I), RNA 16S (16S ribosomal RNA), CytB (Cytochrome b), and Control Region (DLoop). For the species Dicentrarchus labrax, Katsuwonus pelamis, Thunnus sp., primer pairs for DNA barcoding and mini-barcoding, respectively, were designed in silico in this study. For Dicentrarchus labrax, the COI region was identified as the most suitable for species identification, while for Katsuwonus pelamis and Thunnus spp., the control region (CR) was chosen based on the literature [22]. All nucleotide sequences of the COI gene and control region (CR) were obtained from NCBI Nucleotide for Dicentrarchus spp., Katsuwonus pelamis, and Thunnus spp., respectively, and were aligned using ClustalW2 software (www.ebi.ac.uk/Tools/msa/clustalw2/ accessed on 1 May 2023). The most conserved regions for Dicentrarchus sp., Katsuwonus pelamis, and Thunnus spp. were identified using Bioedit software and primer pairs specific for the genus Dicentrarchus spp. and Thunnus spp. and the species Katsuwonus pelamis were de novo designed. Primer pairs were tested with Primer–Blast tool available from NCBI (www.ncbi.nlm.nih.gov/tools/primer-blast/ accessed on 1 May 2023) to verify the specificity. Primer sequences are shown in Table 1.
2.3.2. Plant DNA Barcoding
Starting from 2005, mitochondrial, plastid, and nuclear genomes were studied to identify a barcode universal region for plants [39,40,41,42] and four gene regions (rbcL, matK, trnH-psbA, and ITS) have been chosen as the standard DNA barcodes in most applications for plants [43,44,45]. In this study, all of these barcode regions were tested. However, recently, some manuscripts described the efficacy of mini-barcode regions (i.e., the analysis of smaller genome portions—100–150 bp—usually associated with the largest DNA barcodes) for the identification of processed plant extracts [46,47]. Furthermore, in this study, a DNA mini-barcoding barcode (rbcL mini-barcoding) was tested for plant extracts. Primer sequences are shown in Table 1. The different plant regions chosen for each species were defined after an in silico analysis; the sequences for the DNA barcoding marker chosen in this study were downloaded from NCBI Nucleotide database (https://www.ncbi.nlm.nih.gov/nucleotide/ accessed on 1 May 2023). Sequences were aligned using the online tool Muscle (https://www.ebi.ac.uk/Tools/msa/muscle/ accessed on 1 May 2023) and manually edited using Bioedit. Haplotypes were collapsed by using the online tool Fabox (https://users-birc.au.dk/palle/php/fabox/ accessed on 1 May 2023). Finally, each haplotype was compared to the online database using the BLAST algorithm (https://blast.ncbi.nlm.nih.gov/Blast.cgi accessed on 1 May 2023). The best performing plant markers in terms of identification were chosen and selected for the analysis.
2.3.3. Fungi DNA Barcoding
The most common barcode region for fungi identification is ITS [48,49,50]. El Karkouri and colleagues also tested this region for truffles, finding the efficiency for species identification for Tuber spp. Genera [51]. In this study, the ITS barcode region was also chosen for DNA barcoding analysis. Primer sequences are shown in Table 1.
2.3.4. Bacteria DNA Barcoding
For bacteria identification, the 16S rRNA gene is used. It is a common housekeeping gene in all prokaryotic organisms. This gene is the most used in bacterial study because (i) it is present in almost all bacteria, (ii) the function of the 16S rRNA gene over time has not changed, suggesting that random sequence changes are a more accurate measure of the evolution, and (iii) the 16S rRNA gene (1500 bp) is large enough for informatics purposes, even if, for DNA barcoding, a smaller region is analyzed [52]. Primer sequences are shown in Table 1.
2.4. DNA Amplification and Identification
A standard PCR amplification was performed using PCR Mix Plus (A&A Biotechnology, Danzica, Poland) following the manufacturer’s instructions in a 25 μL reaction containing 1 μL 10 mM of each primer and 3 μL of gDNA (about 20–50 ng). PCR cycles differ in relation to the primer pairs used. All the PCR programs are shown Appendix A Table A2. The amplicon was visualized by electrophoresis on agarose gel using 1.5% agarose Tris-acetate-EDTA (TAE) gel. Purified amplicons were bidirectionally sequenced by Sanger at Eurofins Genomics (Ebersberg, Germany). After manual editing, primer removal, and pairwise alignment, all the tested samples’ (Table A2) identities were assessed by adopting a standard comparison approach against the GenBank database with BLASTn [53]. Each barcode sequence was taxonomically assigned to the species with the nearest matches (maximum identity > 99% and query coverage of 100%).
3. Results and Discussion
DNA extraction was successful for 187 specimens out of 212, with high DNA quality and good yield (i.e., 3.2–27.4 ng/μL). The presences in the public databases of the sequences for all the species considered in our study were checked and confirmed. For 25 specimens (11,8% of total), 22 for botanicals and 3 for spices, the extracted DNA was not suitable for the analysis in terms of quantity and quality (Table A1). Concerning the identification, for most of the samples (88.2%), it was possible to identify the species, proving the suitability of the barcode region selected. A total of 45 samples out of 212 were defrauded for a total of 21.2% of detected fraud (Table A1).
Considering the results of this study, the most defrauded products were botanicals, with 28.8% of substitution or contamination (Table 2). To identify the contaminants, further analysis, such as Next Generation Sequencing (NGS), is necessary [54].
Almost all specimens were impossible to identify by morphological methodology, because they were treated, in the form of powder or capsule. This value is in line with the percentage presented by Ichim and colleagues, who showed that 27% of the herbal products commercialized in the global marketplace are adulterated [8]. In the same way, the higher percentage of specimens without detectable DNA (31.4%) were botanicals too (Figure 1, Table 2). This value can be explained considering that more than half of the specimens (51 of 70) undergo industrial pre-treatment, such as high temperatures, use of solvent (ethanol, glycerol), and other industrial treatments such as CO2 supercritical extraction. These industrial processing steps degrade, fragment, and precipitate DNA. In a previous study of ours [46], we evaluated the capability of DNA barcoding identification for botanicals (phytoextract and botanicals). We found that phytoextracts obtained through hydroalcoholic treatment, with the lower percentage of ethanol (<40%) and aqueous processing at low temperature, had a major rate of sequencing and identification success. In this study, we obtained similar results, with a success of identification for liquid aqueous phytoextracts with a low percentage of ethanol (<40%) (i.e., DIF_74, DIF_75, DIF_138, etc.) and an incapability to detect DNA in the other typology of specimens.
After botanicals, the spice sector revealed 28.5% of defrauded products. Our results are in line with the study of Cottenet and colleagues [55]. In most of the non-compliant samples (10 of 12), we did not find a substitution, but a contamination. In some cases (DIF_147 and DIF_173), we were able to identify the genera; in all the remaining samples we obtained multiple sequences and it was impossible to identify any species or genera. This means that the contamination in those samples is high and it is possible that multiple species coexist, as indicated in the literature [56].
Although in the agrifood samples the fraud percentage is lower than botanicals and spices, we face a substitution case of fraud for all the cases. Sample DIF_193 was declared Tuber brumale but was identified as Tuber melanosporum. These two species, although similar, can be distinguished by morphological analysis. Analyzing the gleba, the Tuber melanosporum, known as the black truffle or Périgord truffle, it is very dark, tending to purplish-black and with fine white veins, while the Tuber brumale, commonly known as winter truffle or musky truffle, is grey-brownish with large and sparse veins. The interesting fact is that Tuber melanosporum is more expensive than Tuber brumale. In this case we are facing an involuntary substitution that damages the company but not the consumers. For this reason, the control of the supply chain is important, not only to offer a high-quality product, but also to avoid mistakes that can damage the company itself. The frauds detected in seafood products are not in line with the literature, which declares a percentage of 25–30% of mislabelling [57], while we detected a lower percentage (11.4%). This data can be explained considering that the specimens analyzed were collected directly from the company, assuming that all the samples were compliant. In all cases we faced a case of mislabelling, which is a false claim or distortion of the information provided on the label/packaging. The specimens DIF_009, DIF_069, and DIF_070 were different species of the same genus. They were probably an unintentional fraud. Nevertheless, the specimens DIF_008, DIF_027, DIF_028, DIF_041, and DIF_048 were found to be a totally different genus. The most serious case is the sample DIF_041. This specimen was a processed product and the species was impossible to detect by morphological analysis. It was declared as Theragra chalcogramma but was found to be Lepidopsetta polyxystra. Theragra chalcogramma belongs to the order Gadiformes and is commonly called “Alaska pollock”, while Lepidopsetta polyxystra belongs to the order Pleuronectiformes and is a flat fish commonly called “Northern rock sole”. The criticality of the seafood sector is that companies buy filets or semi-processed fish, unlike other sectors where the starting material is already ground or processed (e.g., botanicals, spices, etc.). This highlights a problem in the control of the supply chain. Finally, the probiotics sector was found to have the lowest percentage of fraud (7.7%). Moreover, we found that the specimen DIF_210, declared Bifidobacterium bifidum, was contaminated with other bacteria. There was probably an unintentional contamination in the production site with another probiotic. Recent studies have demonstrated that probiotic contamination with other probiotics is a common occurrence. For example, a study by Lewis and colleagues found that the contents of many bifidobacterial probiotic products analyzed in their study differ from the ingredient list, sometimes at a subspecies level. Only 1 of the 16 probiotics perfectly matched its bifidobacterial label claims in all samples tested [58]. The implications of probiotic contamination can vary depending on the specific strains involved and the intended use of the probiotic product. In some cases, the presence of unintended probiotics may be harmless or even beneficial. However, there is also a risk of introducing harmful or pathogenic microorganisms that may compromise the safety and efficacy of the probiotic product.
Considering the data from Table 2, it is possible to notice how processed products (such as botanicals, agrifood, and spices) have a significantly higher percentage of fraud. This is because the product, being crushed, transformed, or otherwise not in its whole form, is more difficult to identify morphologically and therefore fraud is more easily carried out.
To conclude, the extraction methods retrieved from the literature and tested in this study seem to be suitable for the chosen products, due to the DNA extraction success of 187 specimens out of 212. Moreover, most of the samples were identified at the species level, so in this study the most suitable barcode regions useful for different types of products were identified. The DNA barcoding approach, given its maturity and its wide application in the last twenty years, could be used in strategic points of the food supply chain: customs, goods management office, but also directly in medium-large companies and in the GDO. Nowadays some companies use DNA analysis to check their suppliers and to ensure customers a quality product, but this technology, although widely used in the scientific environment, is not yet fully accepted by the final consumer. Raising awareness and citizen science will be needed to convey the importance and potential of this approach. In conclusion, this study contributes to the growing body of research on DNA barcoding for species identification in the food industry.
4. Conclusions
Given the results of this study, DNA analysis provides a powerful tool for detecting and identifying contaminants in commercial food products, enabling manufacturers and regulatory authorities to take appropriate action to ensure the quality and safety of these products. The results confirm the suitability and reliability of DNA barcoding and mini-barcoding as fast and effective methods for ensuring quality and safety in the food field. Moreover, techniques such as LAMP, RPA, BAR-RPA, Bar-HRM, and minION have made DNA-based methods more affordable, as they require cheaper instruments and protocols [22,59,60]. However, some challenges, in particular in relation to non-conformances observed in botanicals and spices, remain an issue to investigate. Nevertheless, by addressing these technical and scientific issues and implementing standardized workflows, DNA barcoding can play a crucial role in combating food fraud and enhancing traceability in the food supply chain, thus ensuring consumer confidence and facilitating regulatory compliance.
Author Contributions
Conceptualization, J.F. and V.M.; methodology, T.G. and M.D.; validation, M.D., T.G. and J.F.; investigation, J.F. and V.M.; data curation, J.F., T.G. and V.M.; writing—original draft preparation, J.F.; writing—review and editing, J.F., V.M. and M.L.; supervision, J.F. and V.M.; funding acquisition, F.D.M., M.L. and L.C. All authors have read and agreed to the published version of the manuscript.
Funding
This work was supported by “National Biodiversity Future Center—NBFC” project code CN_00000033, Decreto Direttoriale MUR n.1034 del 17 giugno 2022. The funder had no role in conducting the research and/or during the preparation of the article.
Data Availability Statement
The data presented in this study are available on request from the corresponding author.
Acknowledgments
We are grateful to the companies that kindly provided the specimens for this study. The authors are indebted to Federica Scrivo for advice and support during manuscript preparation.
Conflicts of Interest
Authors Tommaso Gorini, Valerio Mezzasalma, and Fabrizio De Mattia were employed by the company FEM2-Ambiente srl. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Appendix A
Table A1.
In the table are indicated specimen code, the company, the sample typology, the declared and detected species, the field, the extraction typology, and the barcode region chosen.
Table A1.
In the table are indicated specimen code, the company, the sample typology, the declared and detected species, the field, the extraction typology, and the barcode region chosen.
| Specimen Code | Company | Sample Typology | Declared Species | Detected Species | Sector | Extraction | Barcode |
|---|---|---|---|---|---|---|---|
| DIF_001 | Company 1 | Canned olive oil | Thunnus albacares | Thunnus albacares | Seafood | RPP | Control Region |
| DIF_002 | Company 1 | Canned olive oil | Katsuwonis pelamis | Katsuwonus pelamis | Seafood | RPP | Control Region |
| DIF_003 | Company 1 | Canned seed oil | Thunnus albacares | Thunnus albacares | Seafood | RPP | Control Region |
| DIF_004 | Company 1 | Canned olive oil | Thunnus albacares | Thunnus albacares | Seafood | RPP | Control Region |
| DIF_005 | Company 1 | Canned olive oil | Thunnus albacares | Thunnus albacares | Seafood | RPP | Control Region |
| DIF_006 | Company 1 | Brine | Thunnus albacares | Thunnus albacares | Seafood | RPP | Control Region |
| DIF_007 | Company 1 | Canned olive oil | Scomber colias | Scomber colias | Seafood | RPP | ITS |
| DIF_008 | Company 1 | Brine | Katsuwonis pelamis | Thunnus albacares | Seafood | RPP | Control Region |
| DIF_009 | Company 1 | Canned olive oil | Thunnus obesus | Thunnus albacares | Seafood | RPP | Control Region |
| DIF_010 | Company 1 | Canned olive oil | Engraulis engrasicolus | Engraulis engrasicolus | Seafood | TGF | COI |
| DIF_011 | Company 2 | Fillet | Parapenaeus longirostris | Parapenaeus longirostris | Seafood | TGF | COI |
| DIF_012 | Company 2 | Fillet | Litopenaeus vannamei | Litopenaeus vannamei | Seafood | TGF | COI |
| DIF_013 | Company 2 | Fillet | Lates niloticus | Lates niloticus | Seafood | TGF | COI |
| DIF_014 | Company 2 | Burger | Xiphias gladius | Xiphias gladius | Seafood | TGF | COI |
| DIF_015 | Company 2 | Burger | Xiphias gladius | Xiphias gladius | Seafood | TGF | COI |
| DIF_016 | Company 2 | Burger | Oncorhynchus mykiss | Oncorhynchus mykiss | Seafood | TGF | COI |
| DIF_017 | Company 2 | Burger | Salmo salar | Salmo salar | Seafood | TGF | COI |
| DIF_018 | Company 2 | Burger | Thunnus albacares | Thunnus albacares | Seafood | TGF | Control Region |
| DIF_019 | Company 2 | Burger | Oncorhynchus mykiss | Oncorhynchus mykiss | Seafood | TGF | COI |
| DIF_020 | Company 2 | Burger | Oncorhynchus mykiss | Oncorhynchus mykiss | Seafood | TGF | COI |
| DIF_021 | Company 2 | Processed product | Oncorhynchus mykiss | Oncorhynchus mykiss | Seafood | TGF | COI |
| DIF_022 | Company 3 | Fillet | Sepia officinalis | Sepia officinalis | Seafood | TGF | COI |
| DIF_023 | Company 3 | Fillet | Nephrops norvegicus | Nephrops norvegicus | Seafood | TGF | COI |
| DIF_024 | Company 3 | Fillet | Parapenaeus longirostris | Parapaeneus longirostris | Seafood | TGF | COI |
| DIF_025 | Company 3 | Fillet | Aristeomorpha foliacea | Aristeomorpha foliacea | Seafood | TGF | COI |
| DIF_026 | Company 3 | Fillet | Loligo vulgaris | Loligo vulgaris | Seafood | TGF | COI |
| DIF_027 | Company 3 | Fillet | Todarodes sagitattus | Todaropsis eblanae | Seafood | TGF | COI |
| DIF_028 | Company 3 | Fillet | Trigloporus lastoviza | Chelidonichthys cuculus | Seafood | TGF | COI/16S rRNA |
| DIF_029 | Company 3 | Fillet | Merluccius merluccius | Merluccius merluccius | Seafood | TGF | COI |
| DIF_030 | Company 3 | Fillet | Octopus vulgaris | Octopus vulgaris | Seafood | TGF | COI |
| DIF_031 | Company 4 | Processed product | Dicentrarchus labrax | Dicentrarchus labrax | Seafood | TGF | CytB |
| DIF_032 | Company 4 | Processed product | Merluccius gayi | Merluccius gayi | Seafood | TGF | COI |
| DIF_033 | Company 4 | Processed product | Salmo salar | Salmo salar | Seafood | TGF | COI |
| DIF_034 | Company 4 | Processed product | Thunnus albacares | Thunnus albacares | Seafood | TGF | Control Region |
| DIF_035 | Company 4 | Intermediate product | Thunnus albacares | Thunnus albacares | Seafood | TGF | Control Region |
| DIF_036 | Company 4 | Processed product | Thunnus albacares | Thunnus albacares | Seafood | TGF | Control Region |
| DIF_037 | Company 4 | Fillet | Thunnus albacares | Thunnus albacares | Seafood | TGF | Control Region |
| DIF_038 | Company 5 | Fillet | Pleuronectes platessa | Pleuronectes platessa | Seafood | TGF | COI |
| DIF_039 | Company 5 | Brine | Octopus vulgaris | Octoupus vulgaris | Seafood | TGF | COI |
| DIF_040 | Company 5 | Brine | Dosidicus gigas | Dosidicus gigas | Seafood | TGF | COI |
| DIF_041 | Company 5 | Processed product | Theragra chalcogramma | Lepidopsetta polyxystra | Seafood | TGF | COI/16S rRNA |
| DIF_042 | Company 5 | Brine | Sepia officinalis | Sepia officinalis | Seafood | TGF | COI |
| DIF_043 | Company 5 | Brine | Litopenaeus vannamei | Litopenaeus vannamei | Seafood | TGF | COI |
| DIF_044 | Company 5 | Brine | Dosidicus gigas | Dosidicus gigas | Seafood | TGF | COI |
| DIF_045 | Company 5 | Brine | Thunnus albacares | Thunnus albacares | Seafood | TGF | Control Region |
| DIF_046 | Company 5 | Brine | Salmo salar | Salmo salar | Seafood | TGF | COI |
| DIF_047 | Company 5 | Brine | Gadus morhua | Gadus morhua | Seafood | TGF | COI |
| DIF_048 | Company 5 | Brine | Molva spp. | Brosme brosme | Seafood | TGF | COI |
| DIF_049 | Company 5 | Processed product | Merluccius paradoxus | Merluccius paradoxus | Seafood | TGF | COI |
| DIF_050 | Company 7 | Fresh product | Acipenser transmontanus | Acipenser transmontanus | Seafood | TGF | CytB |
| DIF_051 | Company 7 | Fresh product | Acipenser gueldenstaedtii | Acipenser gueldenstaedtii | Seafood | TGF | CytB |
| DIF_052 | Company 7 | Fresh product | Huso huso | Huso huso | Seafood | TGF | CytB |
| DIF_053 | Company 7 | Fresh product | Acipenser naccarii | Acipenser naccarii | Seafood | TGF | CytB |
| DIF_054 | Company 7 | Fresh product | Acipenser baerii | Acipenser baerii/ Acipenser gueldenstaedtii | Seafood | TGF | CytB |
| DIF_055 | Company 7 | Fresh product | Acipenser stellatus | Acipenser stellatus | Seafood | TGF | CytB |
| DIF_056 | Company 8 | Intermediate product | Thunnus spp. | Thunnus albacares | Seafood | TGF | Control Region |
| DIF_057 | Company 8 | Canned olive oil | Thunnus spp. | Thunnus albacares | Seafood | RPP | Control Region |
| DIF_058 | Company 8 | Intermediate product | Thunnus spp. | Thunnus albacares | Seafood | TGF | Control Region |
| DIF_059 | Company 8 | Canned olive oil | Thunnus spp. | Thunnus albacares | Seafood | RPP | Control Region |
| DIF_060 | Company 8 | Intermediate product | Thunnus spp. | Thunnus albacares | Seafood | TGF | Control Region |
| DIF_061 | Company 8 | Canned olive oil | Thunnus spp. | Thunnus albacares | Seafood | RPP | Control Region |
| DIF_062 | Company 8 | Canned olive oil | Engraulis encrasicolus | Engraulis encrasicolus | Seafood | RPP | COI |
| DIF_063 | Company 9 | Fillet | Dentex angolensis Poll & Maul | Dentex angolensis Poll & Maul | Seafood | TGF | COI |
| DIF_064 | Company 9 | Fillet | Synaptura spp. | Synaptura lusitanica | Seafood | TGF | COI |
| DIF_065 | Company 9 | Fillet | Psettodes spp. | Psettodes bennettii | Seafood | TGF | COI |
| DIF_066 | Company 9 | Fillet | Gadus morhua L. | Gadus morhua L. | Seafood | TGF | COI |
| DIF_067 | Company 9 | Fillet | Epinephelus costae Steindachner | Epinephelus costae Steindachner | Seafood | TGF | COI |
| DIF_068 | Company 9 | Fillet | Dosidicus gigas d’Orbigny | Dosidicus gigas d’Orbigny | Seafood | TGF | COI |
| DIF_069 | Company 9 | Processed product | Merluccius capensis Castelnau | Merluccius paradoxus | Seafood | TGF | COI |
| DIF_070 | Company 9 | Processed product | Merluccius hubbsi Marini | Merluccius gayi | Seafood | TGF | COI |
| DIF_071 | Company 10 | Raw plant | Humulus lupulus L. | Humulus lupulus L. | Botanicals | DPQ | ITS |
| DIF_072 | Company 10 | Extraction waste 7% EtOH | Humulus lupulus L. | Humulus lupulus L. | Botanicals | DPQ/CTAB | ITS |
| DIF_073 | Company 10 | Extraction waste 50% EtOH | Humulus lupulus L. | Humulus lupulus L. | Botanicals | DPQ/CTAB | ITS |
| DIF_074 | Company 10 | Liquid phytoextract 7% EtOH | Humulus lupulus L. | Humulus lupulus L. | Botanicals | DPQ/CTAB | ITS |
| DIF_075 | Company 10 | Liquid phytoextract 50% EtOH | Humulus lupulus L. | Humulus lupulus L. | Botanicals | DPQ/CTAB | ITS |
| DIF_076 | Company 11 | Powder | Malva sylvestris L. | Malva sylvestris L. | Botanicals | DPQ | ITS |
| DIF_077 | Company 11 | Powder | Carica papaya L. | Contamination | Botanicals | DPQ | ITS |
| DIF_078 | Company 11 | Powder | Valeriana officinalis L. | Valeriana officinalis L. | Botanicals | DPQ | psbA-trnH |
| DIF_079 | Company 11 | Dry phytoextract | Garcinia cambogia Desr. | Jurinea leptoloba | Botanicals | DPQ/CTAB | ITS |
| DIF_080 | Company 11 | Liquid idroalcolic phytoextract | Vaccinium macrocarpon Aiton | Leersia spp. | Botanicals | DPQ/CTAB | rbcL |
| DIF_081 | Company 11 | Dry phytoextract CO2 supercritical | Magnolia officinalis Rehder & E.H. Wilson | No DNA detected | Botanicals | DPQ/CTAB | ITS |
| DIF_082 | Company 12 | Essential oil | Citrus limon L. | No DNA detected | Botanicals | DPQ/CTAB | ITS |
| DIF_083 | Company 12 | Essential oil | Mentha x piperita L. | Abotilum indicum | Botanicals | DPQ/CTAB | ITS |
| DIF_084 | Company 12 | Essential oil | Citrus sinensis L. | Contamination | Botanicals | DPQ/CTAB | ITS |
| DIF_085 | Company 12 | Liquid gliceric phytoextract | Matricaria chamomilla L. | Sida acuta | Botanicals | DPQ/CTAB | matK |
| DIF_086 | Company 12 | Liquid gliceric phytoextract | Camellia sinensis Kuntze | No DNA detected | Botanicals | DPQ/CTAB | ITS |
| DIF_087 | Company 12 | Liquid gliceric phytoextract | Calendula officinalis L. | No DNA detected | Botanicals | DPQ/CTAB | psbA-trnH |
| DIF_088 | Company 12 | Flour | Oryza sativa L. | Cicer arietinum | Botanicals | DPQ/CTAB | ITS |
| DIF_089 | Company 12 | Flour | Manihot esculenta Crantz | Cicer arietinum | Botanicals | DPQ/CTAB | ITS |
| DIF_090 | Company 12 | Powder | Aloe vera L. | No DNA detected | Botanicals | DPQ/CTAB | psbA-trnH |
| DIF_091 | Company 13 | Raw plant | Cynara cardunculus L. | Cynara cardunculus L. | Botanicals | DPQ | psbA-trnH |
| DIF_092 | Company 13 | Dry acqueous phytoextract | Cynara cardunculus L. | Contamination | Botanicals | DPQ/CTAB | psbA-trnH |
| DIF_093 | Company 14 | Food supplement | Panax ginseng C.A. Meyer | Contamination | Botanicals | DPQ/CTAB | rbcL |
| DIF_094 | Company 14 | Food supplement | Monascus purpureus | Contamination | Botanicals | DPQ/CTAB | ITS |
| DIF_095 | Company 14 | Raw plant | Aloe vera L. | Contamination | Botanicals | DPQ/CTAB | psbA-trnH |
| DIF_096 | Company 15 | Raw plant | Syzygium aromaticum (L.) Merr & L.M. Perry | Contamination | Botanicals | DPQ/CTAB | ITS |
| DIF_097 | Company 15 | Powder | Rhus spp. | No DNA detected | Botanicals | DPQ/CTAB | ITS |
| DIF_098 | Company 15 | Powder | Citrus hystrix DC. | Moniliella suaveolens | Botanicals | DPQ/CTAB | ITS |
| DIF_099 | Company 16 | Food supplement | Phyllanthus niruri L. | No DNA detected | Botanicals | DPQ/CTAB | ITS |
| DIF_100 | Company 16 | Food supplement | Hibiscus sabdariffa L. | No DNA detected | Botanicals | DPQ/CTAB | ITS |
| DIF_101 | Company 16 | Oil | Serenoa repens Small | No DNA detected | Botanicals | DPQ/CTAB | ITS |
| DIF_102 | Company 17 | Raw plant | Cymbopogon citratus Stapf | Cymbopogon citratus Stapf | Botanicals | DPQ | psbA-trnH |
| DIF_103 | Company 17 | Raw plant | Glycyrrhiza glabra L. | Glycyrrhiza glabra L. | Botanicals | DPQ | matK + ITS |
| DIF_104 | Company 17 | Raw plant | Foeniculum vulgare Mill. | Foeniculum vulgare Mill. | Botanicals | DPQ | psbA-trnH |
| DIF_105 | Company 17 | Raw plant | Malva sylvestris L. | Malva sylvestris L. | Botanicals | DPQ | psbA-trnH |
| DIF_106 | Company 17 | Raw plant | Matricaria chamomilla L. | Matricaria chamomilla L. | Botanicals | DPQ | matK |
| DIF_107 | Company 17 | Raw plant | Matricaria chamomilla L. | Matricaria chamomilla L. | Botanicals | DPQ | matK |
| DIF_108 | Company 17 | Raw plant | Foeniculum vulgare Mill. | Foeniculum vulgare Mill. | Botanicals | DPQ | psbA-trnH |
| DIF_109 | Company 17 | Raw plant | Zingiber officinale Roscoe | Zingiber officinale Roscoe | Botanicals | DPQ | ITS |
| DIF_110 | Company 17 | Raw plant | Citrus limon L. | Contamination | Botanicals | DPQ | ITS |
| DIF_111 | Company 17 | Raw plant | Citrus limon L. | Citrus limon L. | Botanicals | DPQ | ITS |
| DIF_112 | Company 18 | Raw plant | Camellia sinensis Kuntze | Camellia sinensis var. sinensis | Botanicals | DPQ | ITS |
| DIF_113 | Company 19 | Liquid phyotoextract 23% EtOH | Althaea officinalis L. | Althaea officinalis L. | Botanicals | DPQ/CTAB | rbcL mini-barcoding |
| DIF_114 | Company 19 | Dry phytoextract CO2 supercritical | Serenoa repens Small | Contamination | Botanicals | DPQ/CTAB | ITS |
| DIF_115 | Company 19 | Liquid gliceric phytoextract | Althaea officinalis L. | No DNA detected | Botanicals | DPQ/CTAB | rbcL |
| DIF_116 | Company 19 | Liquid gliceric phytoextract | Althaea officinalis L. | No DNA detected | Botanicals | DPQ/CTAB | rbcL |
| DIF_117 | Company 19 | Liquid phyotoextract 23% EtOH | Althaea officinalis L. | Althaea officinalis L. | Botanicals | DPQ/CTAB | rbcL mini-barcoding |
| DIF_118 | Company 20 | Dry phyotoextract 23% EtOH | Vaccinium myrtillus L. | No DNA detected | Botanicals | DPQ/CTAB | rbcL |
| DIF_119 | Company 20 | Dry phyotoextract 23% EtOH | Vaccinium myrtillus L. | No DNA detected | Botanicals | DPQ/CTAB | rbcL |
| DIF_120 | Company 20 | Dry phyotoextract | Panax ginseng C.A. Meyer | Contamination | Botanicals | DPQ/CTAB | rbcL |
| DIF_121 | Company 20 | Dry phytoextract | Panax ginseng C.A. Meyer | No DNA detected | Botanicals | DPQ/CTAB | rbcL |
| DIF_122 | Company 20 | Dry phytoextract | Curcuma longa L. | No DNA detected | Botanicals | DPQ/CTAB | ITS |
| DIF_123 | Company 20 | Powder | Malva sylvestris L. | Contamination | Botanicals | DPQ | psbA-trnH |
| DIF_124 | Company 21 | Raw plant | Origanum vulgare L. | Origanum onites | Botanicals | DPQ | ITS |
| DIF_125 | Company 21 | Processed product | Prunus dulcis (Mill.) D.A.Webb | Prunus dulcis (Mill.) D.A.Webb | Botanicals | DPQ | ITS |
| DIF_126 | Company 22 | Dry phytoextract | Magnolia officinalis Rehder & E.H. Wilson | No DNA detected | Botanicals | DPQ/CTAB | ITS |
| DIF_127 | Company 22 | Powder | Plantago ovata Forssk. | Plantago spp. | Botanicals | DPQ | psbA-trnH |
| DIF_128 | Company 22 | Powder | Plantago ovata Forssk. | Plantago ovata | Botanicals | DPQ | psbA-trnH |
| DIF_129 | Company 22 | Dry phytoextract | Elaeis guineensis Jacq. | No DNA detected | Botanicals | DPQ/CTAB | ITS |
| DIF_130 | Company 22 | Dry phytoextract | Carum carvi L. | No DNA detected | Botanicals | DPQ/CTAB | matK |
| DIF_131 | Company 23 | Raw plant | Silybum marianum (L.) Gaertn. | Contamination | Botanicals | DPQ | ITS |
| DIF_132 | Company 23 | Dry phytoextract | Silybum marianum (L.) Gaertn. | No DNA detected | Botanicals | DPQ/CTAB | ITS |
| DIF_133 | Company 24 | Powder | Plantago ovata Forssk. | Plantago ovata Forssk. | Botanicals | DPQ | psbA-trnH |
| DIF_134 | Company 25 | Raw plant | Cymbopogon citratus Stapf | Cymbopogon citratus Stapf | Botanicals | DPQ | psbA-trnH |
| DIF_135 | Company 25 | Raw plant | Citrus limon L. | Citrus limon L. | Botanicals | DPQ | ITS |
| DIF_136 | Company 26 | Powder | Crocus sativus L. | Contamination | Botanicals | DPQ | matK + ITS |
| DIF_137 | Company 29 | Extraction waste | Zingiber officinale Roscoe | No DNA detected | Botanicals | DPQ/CTAB | ITS |
| DIF_138 | Company 29 | Liquid acqueous phytoexctract | Zingiber officinale Roscoe | Zingiber officinale Roscoe | Botanicals | DPQ/CTAB | ITS |
| DIF_139 | Company 29 | Essential oil | Zingiber officinale Roscoe | No DNA detected | Botanicals | DPQ/CTAB | ITS |
| DIF_140 | Company 30 | Liquid phytoexctract | Panax ginseng C.A. Meyer | No DNA detected | Botanicals | DPQ/CTAB | rbcL |
| DIF_141 | Company 15 | Powder | Cinnamomum verum J.Presl | Contamination | Spice | DPQ | matK + psbA-trnH |
| DIF_142 | Company 15 | Raw plant | Cinnamomum verum J.Presl | Cinnamomum spp. | Spice | DPQ | matK + psbA-trnH |
| DIF_143 | Company 15 | Raw plant | Piper borbonense C. DC. | Piper guineense | Spice | DPQ | ITS |
| DIF_144 | Company 15 | Raw plant | Vanilla planifolia Jacks. ex Andrews | Contamination | Spice | DPQ | ITS |
| DIF_145 | Company 15 | Raw plant | Vanilla planifolia Jacks. ex Andrews | No DNA detected | Spice | DPQ/CTAB | ITS |
| DIF_146 | Company 26 | Powder | Curcuma longa L. | Contamination | Spice | DPQ | ITS |
| DIF_147 | Company 26 | Powder | Curcuma longa L. | Curcuma spp. | Spice | DPQ | ITS |
| DIF_148 | Company 26 | Raw plant | Cinnamomum cassia J.Presl | Cinnamomum cassia J.Presl | Spice | DPQ | matK + psbA-trnH |
| DIF_149 | Company 26 | Raw plant | Cinnamomum verum J.Presl | Cinnamomum verum J.Presl | Spice | DPQ | matK + psbA-trnH |
| DIF_150 | Company 26 | Powder | Cinnamomum cassia J.Presl | Cinnamomum cassia J.Presl | Spice | DPQ | matK + psbA-trnH |
| DIF_151 | Company 26 | Raw plant | Cinnamomum tamala T.Nees & Eberm. | Cinnamomum tamala T.Nees & Eberm. | Spice | DPQ | matK + psbA-trnH |
| DIF_152 | Company 26 | Powder | Zingiber officinale Roscoe | Contamination | Spice | DPQ | ITS |
| DIF_153 | Company 11 | Powder | Curcuma longa L. | Curcuma longa L. | Spice | DPQ | ITS |
| DIF_154 | Company 26 | Powder | Crocus sativus L. | Crocus sativus L. | Spice | DPQ | matK + ITS |
| DIF_155 | Company 26 | Raw plant | Crocus sativus L. | Crocus sativus L. | Spice | DPQ | matK + ITS |
| DIF_156 | Company 26 | Powder | Capsicum spp. | Contamination | Spice | DPQ | ITS |
| DIF_157 | Company 26 | Raw plant | Piper nigrum L. | Contamination | Spice | DPQ | ITS |
| DIF_158 | Company 26 | Powder | Capsicum spp. | Capiscum spp. | Spice | DPQ | ITS |
| DIF_159 | Company 26 | Raw plant | Vanilla planifolia Jacks. ex Andrews | Contamination | Spice | DPQ | rbcL |
| DIF_160 | Company 26 | Raw plant | Crocus sativus L. | Crocus sativus L. | Spice | DPQ | matK + ITS |
| DIF_161 | Company 27 | Dry phytoextract 30% EtOH | Crocus sativus L. | Contamination | Spice | DPQ/CTAB | matK + ITS |
| DIF_162 | Company 15 | Powder | Capsicum spp. | Capsicum spp. | Spice | DPQ | ITS |
| DIF_163 | Company 15 | Powder | Myristica fragrans Houtt. | Cuminum cyminum | Spice | DPQ | ITS |
| DIF_164 | Company 15 | Powder | Curcuma longa L. | Curcuma longa L. | Spice | DPQ | ITS |
| DIF_165 | Company 28 | Raw plant | Origanum vulgare L. | Origanum vulgare L. | Spice | DPQ | ITS |
| DIF_166 | Company 29 | Raw plant | Zingiber officinale Roscoe | Zingiber officinale Roscoe | Spice | DPQ | ITS |
| DIF_167 | Company 31 | Raw plant | Piper nigrum L. | Piper nigrum L. | Spice | DPQ | ITS |
| DIF_168 | Company 31 | Raw plant | Piper nigrum L. | Piper nigrum L. | Spice | DPQ | ITS |
| DIF_169 | Company 31 | Raw plant | Allium cepa L. | Allium cepa L. | Spice | DPQ | ITS |
| DIF_170 | Company 31 | Powder | Allium cepa L. | Allium cepa L. | Spice | DPQ | ITS |
| DIF_171 | Company 31 | Powder | Capsicum spp. | Capsicum spp. | Spice | DPQ | ITS |
| DIF_172 | Company 31 | Powder | Capsicum spp. | Capsicum spp. | Spice | DPQ | ITS |
| DIF_173 | Company 31 | Powder | Curcuma longa L. | Curcuma spp. | Spice | DPQ | ITS |
| DIF_174 | Company 31 | Powder | Curcuma longa L. | Curcuma longa L. | Spice | DPQ | ITS |
| DIF_175 | Company 31 | Powder | Elettaria cardamomum (L.) Maton | Elettaria cardamomum (L.) Maton | Spice | DPQ | ITS |
| DIF_176 | Company 31 | Powder | Elettaria cardamomum (L.) Maton | Elettaria cardamomum (L.) Maton | Spice | DPQ | ITS |
| DIF_177 | Company 31 | Powder | Cinnamomum cassia J.Presl | No DNA detected | Spice | DPQ | matK + psbA-trnH |
| DIF_178 | Company 32 | Powder | Cinnamomum cassia J.Presl | No DNA detected | Spice | DPQ | matK + psbA-trnH |
| DIF_179 | Company 32 | Raw plant | Ocimum basilicum L. | Ocimum basilicum L. | Spice | DPQ | ITS |
| DIF_180 | Company 32 | Powder | Myristica spp. | Myristica fragrans | Spice | DPQ | ITS |
| DIF_181 | Company 32 | Powder | Capsicum annuum L. | Capsicum spp. | Spice | DPQ | ITS |
| DIF_182 | Company 32 | Raw plant | Piper nigrum L. | Piper nigrum L. | Spice | DPQ | ITS |
| DIF_183 | Company 33 | Powder | Fragaria spp. | Fragaria spp. | Agrifood | DPQ | ITS |
| DIF_184 | Company 34 | Fresh product | Tuber melanosporum vitt. | Tuber melanosporum vitt. | Agrifood | DPQ | ITS |
| DIF_185 | Company 34 | Fresh product | Tuber aestivum vitt. | Tuber aestivum vitt. | Agrifood | DPQ | ITS |
| DIF_186 | Company 34 | Fresh product | Tuber magnatum pico | Tuber magnatum pico | Agrifood | DPQ | ITS |
| DIF_187 | Company 34 | Fresh product | Tuber uncinatum chatin | Tuber uncinatum chatin | Agrifood | DPQ | ITS |
| DIF_188 | Company 34 | Fresh product | Tuber albidum pico | Tuber albidum pico | Agrifood | DPQ | ITS |
| DIF_189 | Company 34 | Fresh product | Tuber aestivum vitt. | Tuber aestivum vitt. | Agrifood | DPQ | ITS |
| DIF_190 | Company 34 | Fresh product | Tuber albidum pico | Tuber albidum pico | Agrifood | DPQ | ITS |
| DIF_191 | Company 34 | Fresh product | Tuber uncinatum chatin | Tuber uncinatum/aestivum | Agrifood | DPQ | ITS |
| DIF_192 | Company 34 | Fresh product | Tuber magnatum Pico. | Tuber magnatum Pico. | Agrifood | DPQ | ITS |
| DIF_193 | Company 34 | Fresh product | Tuber brumale Vitt. | Tuber melanosporum | Agrifood | DPQ | ITS |
| DIF_194 | Company 34 | Fresh product | Tuber mesentericum Vitt. | Tuber mesentericum | Agrifood | DPQ | ITS |
| DIF_195 | Company 34 | Fresh product | Tuber brumale Vitt. | Tuber brumale Vitt. | Agrifood | DPQ | ITS |
| DIF_196 | Company 15 | Fresh product | Theobroma cacao L. | Theobroma cacao L. | Agrifood | DPQ | ITS |
| DIF_197 | Company 11 | Powder | Carica papaya L. | Prunus spp. | Agrifood | DPQ | ITS |
| DIF_198 | Company 35 | Flour | Oryza sativa L. | Cicer arietinum | Agrifood | DPQ | ITS |
| DIF_199 | Company 35 | Flour | Oryza sativa L. | Cicer arietinum | Agrifood | DPQ | ITS |
| DIF_200 | Company 24 | Food supplement liophilized | Lactobacillus paracasei | Lactobacillus paracasei | Probiotics | QAQ | 16S rRNA |
| DIF_201 | Company 36 | Food supplement liophilized | Lactobacillus gasseri | Lactobacillus gasseri | Probiotics | QAQ | 16S rRNA |
| DIF_202 | Company 36 | Food supplement liophilized | Lactobacillus gasseri | Lactobacillus gasseri | Probiotics | QAQ | 16S rRNA |
| DIF_203 | Company 36 | Food supplement liophilized | Lactobacillus reuteri | Lactobacillus reuteri | Probiotics | QAQ | 16S rRNA |
| DIF_204 | Company 36 | Food supplement liophilized | Lactobacillus paracasei | Lactobacillus paracasei | Probiotics | QAQ | 16S rRNA |
| DIF_205 | Company 37 | Food supplement liophilized | Lactobacillus paracasei | Lactobacillus paracasei | Probiotics | QAQ | 16S rRNA |
| DIF_206 | Company 37 | Food supplement liophilized | Lactobacillus acidophilus | Lactobacillus acidophilus | Probiotics | QAQ | 16S rRNA |
| DIF_207 | Company 37 | Food supplement liophilized | Lactobacillus acidophilus | Lactobacillus acidophilus | Probiotics | QAQ | 16S rRNA |
| DIF_208 | Company 37 | Food supplement liophilized | Bifidobacterium lactis | Bifidobacterium lactis | Probiotics | QAQ | 16S rRNA |
| DIF_209 | Company 37 | Food supplement liophilized | Bifidobacterium lactis | Bifidobacterium lactis | Probiotics | QAQ | 16S rRNA |
| DIF_210 | Company 38 | Food supplement liophilized | Bifidobacterium bifidum | Contamination | Probiotics | QAQ | 16S rRNA |
| DIF_211 | Company 38 | Food supplement liophilized | Bifidobacterium bifidum | Bifidobacterium bifidum | Probiotics | QAQ | 16S rRNA |
| DIF_212 | Company 38 | Food supplement liophilized | Bifidobacterium bifidum | Bifidobacterium bifidum | Probiotics | QAQ | 16S rRNA |
Table A2.
In the table are indicated the PCR program for all the couples of primers used in the study.
Table A2.
In the table are indicated the PCR program for all the couples of primers used in the study.
| Cox1_Ward_FishF1 Cox1_Ward_FishR1 | Cox1_Ward_FishF2 Cox1_Ward_FishR2 | LCO 1490 HCO 2198 | 16sar-L 16sbr_H | GLUDG C61221H | Tuna_CR_F Tuna_CR_R | Tuna_CR_F Tuna_minibar_R2 | Sco5S_F Sco5S_R | Katw_F Katw_R | Dlab_F Dlab_R | rbcL_1F rbcL724R | rbcL 1 rbcL B | matK_3F_KIM matK_1R_KIM | psbA trnH | ITS-p5 ITS-u4 | ITS3_KYO2 ITS-4 | P0 P6 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Initial step | 94 °C for 3′ | 94 °C for 3′ | 94 °C for 3′ | 94 °C for 3′ | 94 °C for 3′ | 94 °C for 3′ | 94 °C for 3′ | 94 °C for 3′ | 94 °C for 3′ | 94 °C for 3′ | 94 °C for 3′ | 94 °C for 3′ | 94 °C for 3′ | 94 °C for 3′ | 94 °C for 3′ | 94 °C for 3′ | 94 °C for 3′ |
| N. of cycles | 35 | 35 | 35 | 40 | 35 | 35 | 35 | 35 | 35 | 30 | 35 | 35 | 35 | 35 | 35 | 35 | 33 |
| Denaturation | 94 °C for 25″ | 94 °C for 25″ | 94 °C for 1′ | 94 °C for 25″ | 94 °C for 1′ | 94 °C for 30″ | 94 °C for 30″ | 94 °C for 45″ | 94 °C for 30″ | 94 °C for 30″ | 94 °C for 45″ | 94 °C for 45″ | 94 °C for 45″ | 94 °C for 45″ | 94 °C for 45″ | 94 °C for 45″ | 94 °C for 20″ |
| Annealing | 55 °C for 25″ | 55 °C for 25″ | 47 °C for 90″ | 57 °C for 15″ | 52 °C for 1′ | 58 °C for 40″ | 52 °C for 40″ | 48 °C for 45″ | 54 °C for 40″ | 59 °C for 40″ | 50 °C for 30″ | 50 °C for 30″ | 53 °C for 30″ | 53 °C for 30″ | 55 °C for 30″ | 55 °C for 30″ | 54 °C for 30″ |
| Extention | 72 °C for 1′ | 72 °C for 1′ | 72 °C for 25″ | 72 °C for 20″ | 72 °C for 3′ | 72 °C for 1′ | 72 °C for 1′ | 72 °C for 1′ | 72 °C for 1′ | 72 °C for 1′ | 72 °C for 1′ | 72 °C for 1′ | 72 °C for 1′ | 72 °C for 1′ | 72 °C for 1′ | 72 °C for 1′ | 72 °C for 45″ |
| Final elongation | 72 °C for 10′ | 72 °C for 10′ | 72 °C for 7′ | 72 °C for 10′ | 70 °C for 5′ | 72 °C for 10′ | 72 °C for 10′ | 72 °C for 7′ | 72 °C for 10′ | 72 °C for 10′ | 72 °C for 7′ | 72 °C for 7′ | 72 °C for 7′ | 72 °C for 7′ | 72 °C for 7′ | 72 °C for 7′ | 72 °C for 5′ |
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Figure 1.
Infographics represent the percentage of compliant, non-compliant, and specimens with no DNA detected (C, NC and ND) for all the field analyzed.
Figure 1.
Infographics represent the percentage of compliant, non-compliant, and specimens with no DNA detected (C, NC and ND) for all the field analyzed.
Table 1.
List of primer name, gene target, primer sequence (5′->3′), bp of the fragment obtained, annealing temperature, taxonomic target, and reference.
Table 1.
List of primer name, gene target, primer sequence (5′->3′), bp of the fragment obtained, annealing temperature, taxonomic target, and reference.
| Primer Name | Gene | Primer Sequence (5′->3′) | bp | Ta °C | Target | Reference |
|---|---|---|---|---|---|---|
| Cox1_Ward_FishF1 | COI | F: TCAACCAACCACAAAGACATTGGCAC | 655 | 55 °C | Bony fish | [27] |
| Cox1_Ward_FishR1 | R: TAGACTTCTGGGTGGCCAAAGAATCA | |||||
| Cox1_Ward_FishF2 | COI | F: TCGACTAATCATAAAGATATCGGCAC | 616 | 55 °C | Bony fish | [27] |
| Cox1_Ward_FishR2 | R: ACTTCAGGGTGACCGAAGAATCAGAA | |||||
| LCO 1490 | COI | F: GGTCAACAAATCATAAAGATATTGG | 700 | 47 °C | Crustaceans and cephalopods | [28] |
| HCO 2198 | R: TAAACTTCAGGGTGACCAAAAAATCA | |||||
| 16sar-L | 16S rRNA | F: CGCCTGTTTAYCAAAAACAT | 571 | 57 °C | Animal universal | [29] |
| 16sbr_H | R: CCGGTCTGAACTCAGATCACGT | |||||
| GLUDG | Cytb | F: TGACTTGAARAACCAYCGTTG | 1140 | 52 °C | Animal universal | [30] |
| C61221H | R: CTCCAGTCTTCGRCTTACAAG | |||||
| Tuna_CR_F | CR | F: GCAYGTACATATATGTAAYTACACC | 236 | 58 °C | Thunnus spp. | [31] |
| Tuna_CR_R | R: CTGGATGGTAGGYTCTTACTGCG | |||||
| Tuna_CR_F | CR | F: GCAYGTACATATATGTAAYTACACC | 80 | 52 °C | Thunnus spp. | [31]/This study |
| Tuna_minibar_R2 | R: GAYATATGAATAKTTWSRTAC | |||||
| Sco5S_F | ITS | F: CTCACTGTTACAGCCTG | 120 | 48 °C | Scomber spp. | [19] |
| Sco5S_R | R: CAAACACATGCTATCCTT | |||||
| Katw_F | CR | F: GCGAGATYTAAGACCTACCACG | 80 | 54 °C | Katswonus spp. | This study |
| Katw_R | R: GAGCTGGTTGGTCTCTT | |||||
| Dlab_F | COI | F: TCTTATTCTCCCCGGGTTCG | 186 | 59 °C | Dicentrarchus spp. | This study |
| Dlab_R | R: GATGTGAAGTATGCGCGTGT | |||||
| rbcL_1F | rbcL | F: ATGTCACCACAAACAGAAAC | 743 | 50 °C | Plants universal | [31,32] |
| rbcL724R | R: TCGCATGTACCTGCAGTAGC | |||||
| rbcL 1 | rbcL | F: TTGGCAGCATTYCGAGTAACTCC | 226 | 50 °C | Plants universal | [33] |
| rbcL B | R: AACCYTCTTCAAAAAGGTC | |||||
| matK_3F_KIM | matK | F: CGTACAGTACTTTTGTGTTTACGAG | 636 | 53 °C | Plants universal | [34] |
| matK_1R_KIM | R: ACCCAGTCCATCTGGAAATCTTGGTT | |||||
| psbA | psbA-trnH | F: GTTATGCATGAACGTAATGCTC | 300–600 | 53 °C | Plants universal | [35] |
| trnH | R: CGCGCATGGTGGATTCACAATCC | |||||
| ITS-p5 | ITS | F: CCTTATCAYTTAGAGGAAGGAG | 300–750 | 55 °C | Plants universal | [36] |
| ITS-u4 | R: RGTTTCTTTTCCTCCGCTTA | |||||
| ITS3_KYO2 | ITS | F: GATGAAGAACGYAGYRAA | 300–500 | 55 °C | Fungi | [37] |
| ITS-4 | R: RGTTTCTTTTCCTCCGCTTA | |||||
| P0 | 16S rRNA | F: GAGAGTTTGATCCTGGCTCAG | 1540 | 54 °C | Bacteria | [38] |
| P6 | R: CTACGGCTACCTTGTTACGA |
Table 2.
In the table are indicated the number of specimens analyzed divided into compliant, non-compliant, and samples where DNA was not detected, also expressed in percentage.
Table 2.
In the table are indicated the number of specimens analyzed divided into compliant, non-compliant, and samples where DNA was not detected, also expressed in percentage.
| Specimens’ Typology | Collected Specimens | Sector | Compliant (Percentage) | Non-Compliant (Percentage) | No DNA Detected (Percentage) |
|---|---|---|---|---|---|
| Fresh/raw | 6 | Seafood | 6 (100%) | / | / |
| Intermediate | 4 | 4 (100%) | / | / | |
| Processed | 60 | 52 (86.6%) | 8 (13.3%) | / | |
| Total | 70 | 62 (88.5%) | 8 (11.5%) | / | |
| Fresh/raw | 19 | Botanicals | 14 (73.7%) | 5 (26.3%) | / |
| Intermediate | 3 | 3 (100%) | / | / | |
| Processed | 51 | 13 (25.5%) | 16 (31.3%) | 22 (43.2%) | |
| Total | 73 | 30 (41.1%) | 21 (28.8%) | 22 (30.1%) | |
| Fresh/raw | 13 | Agrifood | 12 (92.3%) | 1 (7.7%) | 0 |
| Intermediate | / | / | / | 0 | |
| Processed | 4 | 1 (25%) | 3 (75%) | 0 | |
| Total | 17 | 14 (76.5%) | 3 (23.5%) | / | |
| Fresh/raw | 18 | Spice | 13 (72.2%) | 4 (22.2%) | 1 (5.6%) |
| Intermediate | / | / | / | / | |
| Processed | 24 | 14 (58.3%) | 8 (33.3%) | 2 (8.3%) | |
| Total | 42 | 27 (64.5%) | 12 (28.5%) | 3 (7%) | |
| Fresh/raw | / | Probiotics | / | / | / |
| Intermediate | / | / | / | / | |
| Processed | 13 | 12 (92.5%) | 1 (7.5%) | / | |
| Total | 13 | 12 (92.5%) | 1 (7.5%) | / |
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Gorini, T.; Mezzasalma, V.; Deligia, M.; De Mattia, F.; Campone, L.; Labra, M.; Frigerio, J. Check Your Shopping Cart: DNA Barcoding and Mini-Barcoding for Food Authentication. Foods 2023, 12, 2392. https://doi.org/10.3390/foods12122392
AMA Style
Gorini T, Mezzasalma V, Deligia M, De Mattia F, Campone L, Labra M, Frigerio J. Check Your Shopping Cart: DNA Barcoding and Mini-Barcoding for Food Authentication. Foods. 2023; 12(12):2392. https://doi.org/10.3390/foods12122392
Chicago/Turabian StyleGorini, Tommaso, Valerio Mezzasalma, Marta Deligia, Fabrizio De Mattia, Luca Campone, Massimo Labra, and Jessica Frigerio. 2023. "Check Your Shopping Cart: DNA Barcoding and Mini-Barcoding for Food Authentication" Foods 12, no. 12: 2392. https://doi.org/10.3390/foods12122392
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