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Let’s Talk Science Youth Action Project DNA Barcoding Market Survey Results This presentation summarizes the results of the Let’s Talk Science youth impact.

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Presentation on theme: "Let’s Talk Science Youth Action Project DNA Barcoding Market Survey Results This presentation summarizes the results of the Let’s Talk Science youth impact."— Presentation transcript:

1 Let’s Talk Science Youth Action Project DNA Barcoding Market Survey Results
This presentation summarizes the results of the Let’s Talk Science youth impact action project using DNA barcoding in a seafood market survey.

2 What is a Market Survey? $30.66/kg $18.19/kg Tilapia Red Snapper
Click 1: Whole fish are usually easy to identify to the species level. Click 2: However, one they are processed it can become very difficult to identify the species. Click 3: There are many different potential impacts of mislabeling fish products. The most noticeable is the price difference between many species, like the two in this example. However, there can also be health, conservation and lifestyle implications when fish species are incorrectly labeled, whether purposefully or not. A market survey can be used to determine if any species are incorrectly identified in the food products collected. $30.66/kg $18.19/kg

3 Sampling 16 different market names were targeted: Snapper Cod Halibut
Shark Yellowtail Catfish Bass Pickerel Whitefish Perch Orange Roughy Sole Haddock Pollock Scallops Mussels 16 different common market names were targeted in this survey. Samples were limited to fresh or frozen products, rather than cooked or otherwise processed.

4 Sampling Seafood was purchased at local markets, restaurants and grocery stores Small tissue samples were taken by students Preserved in 95% ethanol Shipped to the Biodiversity Institute at the University of Guelph Read slide … Students also filled out a data collection form at the time of sampling indicating the market name, and other key features of each product.

5 Specimen Tissue Sample DNA Barcoding Extract DNA PCR Amplify Sequence The DNA barcoding process was continued at the Biodiversity Institute at the University of Guleph once the tissue samples arrived. Samples were arrayed into high-throughput plates and went through standard DNA barcoding protocols for DNA extraction, PCR and DNA sequencing.

6 DNA Barcoding The resulting DNA barcode sequences were uploaded to an project on the online DNA barcode database – the Barcode of Life DataSystem, or BOLD. By comparing entries from this project to other sequences in the database, the species corresponding to each product could be identified, thereby determining whether the product was correctly labeled.

7 Results Overview 332 specimens were analyzed
302 yielded a DNA barcode sequence 92% success According to CFIA Fish List 48 DNA barcodes did not match market name listed (14%) Relatively low rate of mislabeling Read point 1, and point 2. This means 92% of samples were successfully DNA barcoded. For all 332 samples, The CFIA Fish List was used to determine if the scientific name matching the DNA barcode sequence was acceptable for the market name recorded by the students for each product. Of these, there were 48 instances where the species identified from the DNA barcode sequence did not match the market name on the product label according to CFIA guidelines for market names and corresponding species. 14% mislabeling is lower than what has been found in many previous market surveys.

8 Categories of Potential Mislabeling
Identified species on CFIA list, and doesn’t match market name (20) 2. Identified fish not on CFIA list and common name doesn’t match market name (7) 3. Identified fish is not on the CFIA fish list, but common name does match (18) There were 4 different categories of potential mislabeling that each case could be classified in. The first was that the species identified using DNA barcoding did not match the market name for the product, and that the actual species name was on the CFIA fish list. 20 products were in this category. The second was that the species identified using DNA barcoding was NOT on the CFIA fish list, and additionally, the common name for the species did not match the market name of the product. 7 products were in this category. The third category was when the species identified using DNA barcoding was NOT on the CIFA list, but the common name did match the market name. 18 products were in this category. Finally, there were 3 products whose sequences did not have a match on BOLD. The next few slides highlight examples from each of these categories. 4. No Match in BOLD (3)

9 Category 1: On list, mislabeled
Included instances of tilapia and Norway redfish labeled as red snapper and Haddock and Pollock labeled as cod Market names mislabeled: bass, whitefish, perch, cod, catfish, red snapper, pacific salmon and Chilean sea bass Read left side of slide. The market names mislabeled in this category included: (read list).

10 Category 1: On list, mislabeled
Example 1: LTSMS590 Market Label: halibut DNA barcode match: Hyporthodus flavolimbatus (Yellowfinned grouper) On the IUCN vulnerable status One of the examples in this category was labeled as halibut. However, the DNA barcode sequence matched Hyporthodus flavolimbatus, the yellowfinned grouper, which is listed by the IUCN as vulnerable.

11 Category 1: On list, mislabeled
Example 2: LTSMS285 Market Label: red snapper DNA barcode match: Oreochromis sp. (tilapia) Farmed tilapia: Pollution depending on region farmed Environmental impacts of farming practices Fatty acid content Another example is red snapper substituted with tilapia. The economic implications of this were discussed at the beginning of this presentation. However, there are also potential health and conservation impacts from farmed fish such as tilapia. In this case, this includes potential pollutants depending on the region farmed, as well as carbon monoxide used to maintain the colour of the fish. There can also be environmental impacts from fish farming if not practiced responsibly. Finally, the level of omega 3 – the healthy fat found in fish - in tilapia is drastically lower than in other species.

12 Category 2: Not on list, mislabeled
Included further instances of mislabeled snapper, red snapper, and cod Also 2 instances of Mexican River Gizzard Shad (Dorosoma anale) labeled as tilapia This category included further examples of mislabeled snapper, red snapper and cod. There were also 2 instances of mislabeled tilapia. Both seem to have been replaced with Mexican River Gizzard Shad. This is interesting, as tilapia is already a low cost fish.

13 Category 3: Not on list, mislabeled?
Example 1: LTSMS647 Product labeled as Sole DNA barcode matches Lepidopsetta polyxystra Northern Rock Sole Not on CFIA list, but still a type of sole many market names encompass many different species. The next 2 examples are still instances of mislabeling as the CFIA does not allow them to be sold under any market name according to their fish list. However, this likely does not represent fraudulent labeling and may rather be due to issues with nomenclature and compliance with the CFIA Fish List. Read example 1.

14 Category 3: Not on list, mislabeled?
Example 2: LTSMS826 Product labeled as Shark DNA barcode matches Carcharhinus limbatus Blacktip Shark Not on CFIA list, but still a type of shark Read example. Again, this is technically mislabeled as this species of shark is not on the CFIA fish list. However, from a general perspective, the market name was not incorrect, and it was not fraudulently sold. This brings up another important point related to nomenclature – when market names are incorrect to begin with. For example, Chilean sea bass is not a recognized market name in Canada, yet some products in this survey were purchased with this label.

15 Category 4: No Match Of the three products with no match:
One was likely bacterial contamination Two others identified using GenBank as Japanese Anchovy DNA barcodes from three products had no match in BOLD. Read slide.

16 Supporters & Partners This project was made possible thanks to the following supporters & partners: A big thank you to Let’s Talk Science, CurioCity, BIO, and Mitacs who have made this project possible!


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