Mislabeling of Commercial Atlantic Cod (Gadus Morhua) Products in Spain Joshua Helgoe University of South Carolina

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2016 Mislabeling Of Commercial Atlantic Cod (Gadus Morhua) Products In Spain Joshua Helgoe University of South Carolina

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This Open Access Thesis is brought to you by Scholar Commons. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of Scholar Commons. For more information, please contact [email protected]. MISLABELING OF COMMERCIAL ATLANTIC COD (GADUS MORHUA) PRODUCTS IN SPAIN

Joshua Helgoe

Bachelor of Science University of South Carolina, 2015

Submitted in Partial Fulfillment of the Requirements

For the Degree of Master of Science in

Marine Science

College of Arts and Sciences

University of South Carolina

2016

Accepted by:

Joseph Quattro, Director of Thesis

David Wethey, Reader

Joe Jones, Reader

Lacy Ford, Senior Vice Provost and Dean of Graduate Studies

ACKNOWLEDGEMENTS

I would like to acknowledge everybody in Dr. Quattro’s lab who helped me throughout this entire project including Mark Roberts, Katrina Hounchell, Kate

Levasseur, Emma De Neff, Justin Lewandowsky, and Muhammed Alqatani. I would like to acknowledge the Walker Institute and the Magellan Scholar Program for their generous funding of this project.

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ABSTRACT

The mislabeling of commercial fish products is a pervasive, worldwide problem.

Most consumers of seafood are unaware this issue directly affects them and can even have negative impacts on their health. Mislabeling occurs when a product’s label is inconsistent with its content. Although mislabeling can be unintentional, deliberate mislabeling is a more common trend to increase profits and/or bypass fishing regulations

- a form of economic fraud. Unfortunately, oversight, enforcement, and research are vastly insufficient in relation to the global scale of the problem. In order to add to the small knowledge base on European mislabeling rates, determine if overfished or harmful species have been sold, spread consumer awareness, and hold the industry accountable, tissue samples from everyday commercial products and restaurant servings labeled as

Atlantic cod (bacalao in Spanish) were confirmed as containing cod via DNA sequence- based ‘barcoding’. Atlantic cod samples (n=546) were collected and characterized genetically from supermarkets, markets, and restaurants from eight cities (Madrid,

Salamanca, Santiago de Compostela, Bilbao, Barcelona, Valencia, Granada, and Seville) throughout Spain. The DNA barcoding process used a universal PCR-based assay of the mitochondrial Cytochrome Oxidase-I (COI) and 16s locus using standard primer sequences and PCR conditions that are part of the Fish Barcode of Life initiative. Results indicate a 6.4% mislabeling rate (35/546) with no real statistical evidence of distinct geographic patterns of mislabeling. Common ling (Molva molva), haddock

(Melanogrammus aeglefinus), saithe (Pollachius virens), and Alaskan pollock (Gadus chalocogrammus) were the most common substitutes, while Nile perch (Lates niloticus) and Vietnamese catfish (Pangasianodon hypopthalmus) were the most taxonomically dissimilar substitutes. These results are compared to other similar studies assaying fish products in the European Union and elsewhere.

TABLE OF CONTENTS

Acknowledgements ...... iii

Abstract ...... iv

List of tables ...... viii

List of figures ...... ix

Chapter 1: Background ...... 1

1.1 DNA Barcoding ...... 3

1.2 Related Mislabeling Research ...... 5

1.3 Threat to Public Health ...... 8

1.4 IUU Fishing ...... 10

1.5 Economic Cost of Mislabeling ...... 11

1.6 Disguising Mislabeled Fish ...... 13

1.7 Labeling Regulations ...... 15

1.8 Spain and Cod ...... 16

Chapter 2: Hypotheses ...... 20

2.1 Expected Trends in Mislabeling ...... 20

2.2 Expected Substitutions ...... 20

Chapter 3: Materials and methods ...... 21

3.1 Sample Collection ...... 21

3.2 DNA Isolation and Sequencing ...... 29

3.3 DNA Barcoding ...... 31

3.4 Retesting with 16s ...... 32

3.5 Geographic Analysis ...... 33

Chapter 4: Results ...... 34

4.1 Mislabeling by City ...... 34

4.2 Mislabeling by Product Type ...... 35

4.3 Mislabeling by Location Purchased ...... 40

4.4 Substituted Species Relatedness ...... 41

4.5 Mislabeled Sample Data ...... 43

Chapter 5: Discussion ...... 47

5.1 Characteristics of Spanish Cod Mislabeling ...... 48

5.2 Substituted Species ...... 51

5.3 Geographic Analysis ...... 53

5.4 Who is at Fault? ...... 53

5.5 Broader Context ...... 54

Chapter 6: Conclusion...... 56

References ...... 59

Appendix A: Complete Sample Data ...... 69

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LIST OF TABLES

Table 3.1 Samples collected by city ...... 22

Table 3.2 Samples collected by location purchased ...... 23

Table 3.3 Samples collected by product type ...... 24

Table 4.1 City summary data ...... 34

Table 4.2 Product type summary data...... 35

Table 4.3 Samples sequenced by product type for each city ...... 37

Table 4.4 Samples mislabeled by product type for each city ...... 37

Table 4.5 Mislabeling rate by product type for each city ...... 38

Table 4.6 Location of purchase summary data ...... 40

Table 4.7 Samples sequenced by location of purchase for each city ...... 40

Table 4.8 Samples mislabeled by location of purchase for each city ...... 41

Table 4.9 Mislabeling rate by location of purchase for each city ...... 41

Table 4.10 Relatedness of substituted species ...... 42

Table 4.11 Mislabeling sampling data ...... 43

Table 5.1 Species price comparisons ...... 48

Table A.1 Complete Sample Data ...... 69

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LIST OF FIGURES

Figure 1.1 Source of European eafood imports ...... 18

Figure 3.1 Sampling route...... 21

Figure 3.2 Total samples collected by location purchased ...... 23

Figure 3.3 Proportion of samples sequenced by location purchased for each city ...... 25

Figure 3.4 Total samples collected by their product type ...... 26

Figure 3.5 Proportions of samples sequenced by product type for each city ...... 28

Figure 4.1 Mislabeling occurrences by city ...... 36

Figure 4.2 Palitos de bacalao ...... 38

Figure 4.3 Croquetas de bacalao ...... 39

Figure 4.4 Migas de bacalao ...... 39

CHAPTER 1

BACKGROUND

The method of selling deliberately mislabeled seafood products is a form of commercial seafood fraud, and is a deceptive practice that promotes illegal, unregulated, and undocumented (IUU) fishing, impedes fisheries conservation efforts, damages the economy, and can be dangerous to the consumer (Spink & Moyer 2011). Typically, there is a financial incentive to mislabel by substituting cheaper species (Miller & Mariani

2010). Mislabeling also means that commercially unappealing, toxic, or illegally caught fish species that are otherwise unsellable can be made marketable. Unfortunately, the rapid growth of the seafood industry over the past century has been coupled with a general decrease in traceability of products in the supply chain from catch to customer

(Thompson et al. 2006), thereby facilitating the ability to mislabel and sell substituted fish products. The probability of detecting noncompliance has remained low due to the lack of proper oversight or enforcement of seafood integrity regulations (Buck 2010). It is with the advent of rapid species identification techniques, particularly DNA barcoding

(standardized in 2003), that this previously unrecognized, yet globally pervasive problem of mislabeling is being exposed. Regardless of the growing literature, the extent of this research remains vastly insufficient relative to the ubiquity of mislabeling. The average mislabeling rate across all studied regions and species is 30% (Pardo 2016). Fortunately, each new investigation into mislabeling provides an indispensable view into the densely opaque proceedings of global seafood commerce. Providing high quality mislabeling

research is the first step towards fixing the mislabeling problem. Increased public awareness and mass media alone may directly reduce mislabeling (Mariana et al. 2014), supermarket chains have directly responded to mislabeling research by removing mislabeled products, and finally mislabeling research provides support for the creation of new transparency policies such as the Protect Honest Fisherman Act (H.R. Bill 3282) and the EU Common Organisation of the Markets Policy (EC 2013).

This thesis investigates the mislabeling of commercially sold Atlantic Cod (Gadus morhua) in Spain. Only four studies were found to have analyzed fish mislabeling in

Spain with DNA barcoding prior to the sample collection of this thesis, between August and November 2013, (Asensio et al. 2009; Crego-Prieto 2012; Herrero et al. 2010;

Garcia-Vazquez et al. 2010) despite Spain being the largest consumer of seafood in the

Europe Union (CBI 2015). Atlantic Cod (Gadus morhua) was chosen for this study due to its cultural significance, expensive cost, and the lack of data concerning this commercially popular species in Spain. Instead of pursuing a multispecies investigation as many other studies have done, this research took an intensive single species approach in order to collect a comprehensive dataset across the majority of cod products types and retailers available to consumers. Furthermore, this research collected geographically representative data across eight cities to account for possible variation in mislabeling rates throughout the breadth of the country. The high resolution mislabeling data this research provides adds to the small, yet growing field of literature on mislabeling, and is immediately relevant to the general public, businesses, and policy makers. It is our hope that this work will increase public awareness, substantiate scientific literature on this subject, and support initiatives aimed at improving seafood transparency and

sustainability. This chapter will first provide background on related mislabeling research, on the environmental, health, and economic threats of mislabeling, on Atlantic Cod (G. morhua) consumption, Spain, and mislabeling policy.

1.1 DNA Barcoding

Taxonomically identifying species, until the advent of DNA barcoding, was rarely a simple or an easily accessible process. Traditional taxonomy is typically based off of morphological identification and often requires highly specialized experience (Terlizzi et al. 2003). Taxonomists can generally not identify “more than 0.01% of the estimated 10-

15 million species” (Hebert et al. 2003). Thus, it was estimated that at least 15,000 taxonomists would be necessary to maintain the scientific community’s dependence on morphological identification. Furthermore, this community of specialists has been diminishing (Terlizzi et al 2003).

Genetic identification has long been used to identify species beginning with starch gel electrophoresis (Manwell & Baker 1963). In addition, the accuracy and overall accessibility of genetic sequencing has rapidly increased while the cost of the analysis has substantially decreased (Shendure & Ji 2008). However, without a universal protocol and database by which to compare genetic information, the use of genetics in taxonomy remained isolated to small, specific scientific groups, such as in molecular taxonomy in yeasts (Kurtzman 1994). The imperative to modernize taxonomy, along with the modern accuracy and accessibility of DNA sequence based identification led to the logical proposal by Tautz et al. (2002, 2003) and Hebert et al. (2003) to create a comprehensive database of DNA sequences. The mitochondrial Cytochrome C Oxidase I (CO1) locus

was proposed as a universally applicable genetic marker for standardized comparison due to its appropriate length (~650 base pairs) and adequate interspecific variation between species (Hebert et al. 2003). Hebert’s 2003 proposal for the Barcode of Life Database

(BOLD) received a substantial amount of support in less than a year, and the database has since grown exponentially. As of 2016, the International BOLD contains nearly

5,000,000 CO1 specimens with barcodes from over 250,000 unique species

(http://www.boldsystems.org/index.php/TaxBrowser_Home).

DNA barcoding is particularly applicable to commercial seafood mislabeling research. This is because identifying fish products that lack morphologically identifiable parts (head, scales, fins, etc.) through traditional taxonomic means is usually very difficult or even impossible (Miller & Mariani 2010). In order to sequence DNA, all that is needed is a small tissue sample of the target organism or sample, rather than an entire specimen. Before DNA barcoding was a viable method, the limited data on mislabeling utilized protein analysis and fillet identification guides (Sotelo et al. 1993). DNA analysis is more accurate, sensitive, informative, and reliable than protein analysis especially because proteins degrade easier than DNA does in high heat conditions

(Rasmussen et al. 2008; Lenstra 2003). Fish fillet identification guides exist such as

MarViva (2010) and Oates et al. (1993); however, these guides are not practical for consumers and cannot lead to sufficiently confident species assignments. These guides are best used when there is a need for immediate identification of fresh fish fillets from a particular region. Nearly all seafood mislabeling research has taken place in the past decade, after DNA barcoding became standardized and sequencing databases (BOLD and

GenBank) were comprehensively filled species CO1 sequences.

1.2 Related Mislabeling Research

The rapid increase in mislabeling research since 2008 has uncovered high mislabeling rates across the globe. Approximately 30% of seafood products worldwide are mislabeled (Pardo et al. 2016). The majority of research has focused on gadoid species (39%) (e.g. Hake, Pollock, Cod, Saithe), followed by flatfish (10%) (e.g. plaice, flounder, sole, megrim), percoidei (10%) (e.g. snappers, groupers, whiting), salmonidae

(8%) (e.g. salmon), scombroids (4%) (e.g. barracudas, mackerels, tuna), chondrichthyes

(4%) (e.g. sharks, skate, rays), and other (25%) (Pardo et al. 2016). Gadoid species have been most targated due to their abundance, popularity as commercial fish products, and the ease in which white meat fish can be mislabeled. Although, mislabeling research has been conducted throughout numerous countries and has addressed most popular commercial fish species to atleast some degree, many studies are hindered by small sample sizes and limited geographic scale.

The limited research regarding fish mislabeling in Spain has uncovered high rates across popular commercial species. In 2011, >30% of hake (Merlucciidae), the most commercially popular fish in Spain, was found to be mislabeled (Garcia-Vazquez et al.

2010). A more recent study of hake mislabeling in Spain (n=243) found that the mislabeling rate has oscillated for different hake species from previous years and that there was an increase in diversity of substituted species (Munoz-Colmenero 2015). It was also uncovered that 58 of 70 commercial grouper products from markets throughout

Madrid were mislabeled (Asensio et al. 2009). Of the mislabeled samples 34 were Nile

Perch (Lates niloticus), 13 were wreckfish (Polyprion americanus), and 11 were

unidentified fish products. Recently, a multi-species analysis (n=245) of mislabeling in

Madrid and Asturias revealed a 7.8% mislabeling rate, with 9.6% of cod samples (n=54) mislabeled (Muñoz-Colmenero et al. 2016). Of the cod samples, 89% were from salted products. Finally, megrim mislabeling at landings (n=239) were tested and 40% were inaccurately labeled (Crego-Prieto 2012). All of these studies except for that by Crego-

Prieto (2012) either analyzed a limited geographic area (usually one city or region) or had limited sample sizes. For a country as regionally diverse as Spain, attaining adequate nationally representative mislabeling data demands wider geographical sampling and a large dataset. Furthermore, restaurant samples, although shown to have higher occurrences of mislabeling worldwide (Pardo et al. 2016), were not sampled in Spain aside from a very few samples taken in the study by Muñoz-Colmenero (2016).

Similar studies elsewhere than Spain have reported significant mislabeling occurance. Throughout New York, Los Angeles, Boston, and Miami, 31%-55% of fishes in each city were mislabeled (Warner et al. 2013). The most mislabeled species in Boston was Atlantic cod, which was usually replaced by much cheaper Pacific cod (Gadus macrocephalus) and Alaskan pollock (Theragra chalcogramma). This trend of high mislabeling rates extends to other commercially important species including red snapper, megrim, and tunas. A nationwide US study on mislabeling found slightly more than a quarter of cod samples (28%) tested were mislabeled (32 out of 116) (Warner et al.

2013). In a study of cod fillets and battered cod chunks by the Italian Ministry of

Agriculture, Food and Forestry Policies, 15% of 65 cod fillets were not actually cod, but closely related ling in the family Lotidae. 100% of 40 battered cod chunk products were incorrectly labeled with 28 being haddock (Melanogrammus aeglefinus) and 12 being

cusk (Brosme brosme) (Di Pinto et al. 2013). In South Africa, 178 fish products were tested uncovering half as being mislabeled, including 84% mislabeling of kob

(Argyrosomus japonicas).

A study in Ireland showed mislabeling rates as high as 28% for cod with pollock

(Pollachius pollachius), saithe (Pollachius virens), greater argentine (Argentina silus), and whiting (Merlangius merlangus) being the major replacements (Miller & Mariani et al. 2010). An important question is whether these studies have an impact on public awareness, policy, enforcement, or integrity by the fishing industry. Following the study in Ireland there was a loud and responsive mass media outcry on the subject (Mariani et al. 2010). Very soon after the study was published, the Food Safety Authority of Ireland

(FSAI) began genetically analyzing commercially sold Atlantic cod and haddock. The authority found a significant rate of 19% mislabeling (21 of 111 samples) as well (FSAI

2011). In order to try and determine if the sudden increase in public awareness, or other factors, could have affected the mislabeling problem, a 2013 study was conducted mimicking the exact methods as the former Ireland study 2 years prior (Mariani et al.

2014). The results showed there to be no mislabeling in supermarkets, but that 10 of 24 restaurant samples were mislabeled. Whether the reduction in supermarket mislabeling was due to public awareness, new testing by the government, other factors, or was simply inaccurate due to the small sampling size, is hard to determine. However, the media, public, and governmental reactions that came about because of those findings shows what good research has the potential to accomplish. Culture and media vary between countries, however there was media outcry when the Spanish Hake study was published

as well (Morán 2011). With strong data and proper dissemination, it is possible that this study on cod will instigate meaningful responses to mislabeling in Spain.

Recent studies are showing a fortunate reduction in mislabeling in Europe. A multi-species, nationwide study in France found that only 3.7% of fish were mislabeling after analyzing 371 samples (Bénard-Capelle 2015). Out of a total of 53 fish within the cod family Gadidae, only three were mislabeled. These lower rates have been reaffirmed as no longer being isolated to France, but seem to be occurring throughout Western

Europe (Mariani et al. 2015). It was found that 4.93% of 1563 samples were mislabeled, with only 3.5% of cod samples being mislabeled. Worldwide there was a reduction from

30% mislabeling over the past five years, to 27% in just the past year (Pardo et al. 2016).

1.3 Threat to Public Health

Consumers who purchase mislabeled fish have no knowledge of what the substituted species might be and thus lead the risk of eating potentially toxic or allergenic fish. In 2006, more than 600 people in Hong Kong were sold oilfish instead of codfish that the labels indicated in one of the most serious public health incidents directly caused by mislabeling (Ling et al. 2008, 2009). Oilfish (Ruvettus pretiosus), a snake mackerel, is composed of approximately 25% wax esters. These esters are toxic as they cannot be properly digested and cause a type of diarrhea known specifically as keriorrhea (Ling et al. 2009). In New York in 2008, escolar (Lepidocybium flavobrunneum) was shown to be the primary substitute in dishes labeled as containing “white tuna” (Wong & Hanner

2008). Some countries including Japan and Italy have banned the sale of escolar, whereas others such as the United States and Canada recommend against its sale as well

as provided instructions on how to best consume and sell the fish (Alexander et al. 2004).

Five out of nine samples of white tuna were identified again in New York as being escolar and not albacore (Thunnus alalunga) as they should have been (Lowenstein

2009). Oceana further reported that 84% of mislabeled white tuna samples were escolar

(Warner et al. 2013). In Chicago in 2007, two people who had consumed mislabeled puffer fish had to be treated for tetrodotoxin, a strong neurotoxin (Cohen et al. 2009). In sufficient concentration tetrodotoxin leads to diaphragm paralysis and complete respiratory failure (Ahasan et al. 2004). Those individuals had purchased what was labeled as monkfish at a local market. This incident actually led to a complete recall of monkfish from the supplier by the FDA (Cohen et al. 2009). Although instances such as these in which mislabeled fish led directly to severe illness of a consumer are rare, they represent a very serious risk to consumer health due to the scale on which seafood mislableling occurs.

The other major risk associated with selling mislabeled fish is exposing consumers with allergies to allergenic seafood they are unaware they are purchasing. On average 0.5% of children and 0.3% of adults have finfish allergies (Gupta et al. 2011). In

Canada, 28.6% of accidental exposure to allergenic fish was attributed to improper labeling of the fish (Sheth et al. 2010). Other reasons for accidental exposure included not reading the label or ignoring warnings on packaging. A study in 2010 analyzed the allergenic risk of fish sold in Greece through genetic sequencing and found that 85% of products “contained highly allergenic hake or grenadier species” (Triantiafyllidis et al.

2010). The problem in Greece was not specific mislabeling, but rather that the name

Bakaliaros referred to hake, cod, and gadoid species making it inherently unclear as to

which specific species was being sold. To lower these exposures, labels must be accurate and clear on all products.

Purchasing unknown fish products also means that consumers have no way of knowing the nutritional information about the fish. This is unfair to consumers.

Moreover, eating unknown fish can lead to ingesting excess amounts of methylmercury.

Patagonian toothfish caught from different regions have significantly variable amounts of mercury Marko et al. (2004). Fish that were Marine Stewardship Council (MSC) certified and thus were supposedly from the indicated Southern Georgia fishery, where mercury levels are significantly lower, were being substituted with fish from other fisheries. As a result, MSC certified fish showed mercury levels up to three times higher than expected, and little difference in mercury levels than those not certified.

1.4 IUU fishing

Illegal, Unreported, and Unregulated (IUU) fishing remains a leading threat to the sustainability of fisheries. Up to 46% of the world’s total fish catch derived from IUU fishing (Agnew et al. 2009). These practices are less common in developed countries where fisheries management and enforcement are more established (Agnew et al. 2009), but as long as illegal fishing remains profitable the practice will remain difficult to combat. Many developing countries, where IUU fishing is most common, are also some of the largest exporters of seafood (CBI 2015). Unfortunately, the ability to easily mislabel and sell any fish species provides a simple avenue by which the fishing industry can sell illegally caught fish they may otherwise be unsellable. This undermines conservation efforts to protect fisheries. Furthermore, stricter limitations on catch quotas

for certain species reduces the supply of those fish species while the demand for those species often does not decrease. Thus, the increase in price of those fish makes mislabeling of other cheaper species more profitable.

When restaurants and markets are supplied with mislabeled fish, it can give the fabricated impression that the fish stocks of the species on the label are healthier than they are (Moran & Garcia-Vazquez 2006). When northern red snapper (Lutjanus campechanus), an overfished (Lowerre-Barbieri et al. 2015) and egregiously mislabeled product (Warner et al. 2013; Wong & Hanner 2008), can be seen commonly on restaurant menus it implies that those fish stocks are in good condition.

1.5 Economic Cost of Mislabeling

Although unintentional substitution of seafood products undoubtedly occurs, it is thought to be rare with purposeful substitution being repeatedly acknowledged as the more likely scenario (Miller et al. 2012, Jaquet & Pauly 2008, Munoz-Comenero et al.

2016; Wong & Hanner 2008; Garcia-Vazquez 2010). This is because cheaper fish species have been identified as substitutes for comparatively expensive fish meaning businesses have an economic incentive to mislabel (Munoz-Colmenero et al. 2016;

Garcia-Vazquez 2010). Munoz-Colmenero et al. (2016) observed that eight out of nine mislabeled samples were likely deliberately mislabeled due to clear monetary gain. This is a direct form of economic fraud (Spink & Moyer 2011).

To businesses deliberately mislabeling fish there is direct and tangible economic gain, but only because of the economic loss to the buyer. Furthermore, unfair practices like this imbalance competition between businesses who follow regulations and those

who do not. Businesses mislabeling fish can directly undercut their competition by offering lower prices for substituted fish than their honest competitors who may need to lower their own fish prices below their worth to compensate, who may simply not be able to compete, or may choose to start mislabeling their own product (Warner et al. 2012b).

The latter response may often be the easiest and most profitable response for many businesses in to order to compete with those who are already mislabeling their products.

This contributes to a feedback loop further incentivizing other businesses to mislabel.

Because mislabeling can occur at any point in the supply chain this means that this fraudulent economic tactic can imbalance competition on international to local scales.

Fish fraud also provides avenues by which businesses can circumvent taxes and tariffs that can cost the governments of any affected country substantial losses. In one documented case, the FBI uncovered the import of mislabeled Vietnamese catfish

(Pangasius hypophthalmus) labeled ambiguously as catfish (FDA.gov). This may seem like a small discrepancy; however, in the United States, fish labeled as catfish must be

“American channel catfish (Ictalurus).” This mislabeling led the Sterling Seafood

Corporation to loophole $63 million in federal tariffs (FDA.gov). In the United States,

90% of consumed seafood is imported (NOAA FishWatch 2013). Top importers are

China, Thailand, Canada, Indonesia, Vietnam, and Ecuador – many countries which have weak control on fish exports. For predominating seafood importing countries with little oversight and enforcement of seafood transparity such as the US, seafood mislabeling at the level of international trade likely has siginifcant economic implications.

Hanner et al. (2011), estimated that an international mislabeling rate of 10% alone would lead to an annual 24 billion dollars in fish fraud. That value is likely significantly

higher because the average mislabeling rate is as high as 30% (Pardo et al. 2016).

Reducing fish fraud even by small margins on a large enough scale thus has extensive economic implications for consumers, businesses, and governments.

Fish mislabeling has been shown to be so ubiquitous globally that although though only a small portion of consumers are effected in terms of their health, even minute public health impacts caused by pervasive fish mislabeling can transfer into economic cost. This cost is characteristic in terms of direct health care cost and missed work days. It has been estimated that missed work days in the United States costs the economy $260 billion annually (Davis et al. 2005).

1.6 Disguising Mislabeled fish

Isolated fish meat products are very difficult to identify due to the stark similarities between the meats of many fish species. White fish meat is very commonly mislabeled due to the wide diversity of cheap and easy substitutes that are nearly indistinguishable to the average consumer (Miller & Mariani 2010). Opposingly an entire codfish (G. morhua) for example, is not a product that could be discretely switched due to clear morphological features. Difficult to identify products such as breaded cod, cod fillets, and particularly smoked cod were observed as commonly mislabeling products (Miller & Mariani 2010). The majority of cod products such as fresh, frozen, salted cod, or skin-on or skin-off fillets have little to no clearly identifiable features apart from meat color and skin appearance for skin-on fillets. Skin too however, often looks very similar between closely related species. Therefore, a trend between increasingly inconspicuous fish meat and increased mislabeling should observed.

Closely related species are typically the most common substitutes. Saithe

(Pollachius virens) and pollock (Pollachius pollachius), closely related white fish within the family Gadidae, were found to be the most common substitutes for Atlantic cod (G. morhua) (Miller & Mariani 2010). Other common substitutes for mislabeled cod chunk and cod fillet products were closely related species including pollock (P. Pollachius) as well as cusk (Brosme brosme), which is within the same order Gadiformes (Di Pinto et al.

2013). A review found the most common substitutes for cod to be other closely related species often within the same genus or family (Alaskan pollock, European hake,

European plaice, Atlantic salmon, and tuna (Pardo et al. 2016). European hake species were substituted commonly for cheaper African hake species (Garcia-Vazquez et al.

2010). Red snapper was substituted by 28 different species with the majority of species being substituted either by other species of snapper or rockfish (Warner et al. 2013).

Although fish meat of similar appearance is more often the substitute in similar products, this is not always the case. If fish meat is a component in a restaurant dish, the mix of sauces and other ingredients means that the color, consistency, and taste of the substituted fish can be much more easily disguised. Moreover, many dishes have very small, and thus more difficult to identify pieces of fish meat incorporated into the dish.

Very small pieces of meat would be more difficult to identify as the myomere structure of the meat may be indistinguishable, the taste would be less potent in small quantities

(especially when mixed with other ingredients), and the texture and consistency of the meat could be more variable. For example, in sushi restaurant the high prevalence of mislabeling is less surprising as each piece of sushi is small and generally mixed with other ingredients making the identification of the fish meat very difficult. It was found

that 38% (93 of 243) of restaurant samples and 74% (173 of 241) sushi samples were mislabeled (Hanner et al. 2013). Finally, certain dissimilar substituted species such as

Vietnamese catfish (Pangasius hypophthalmus) that have been repeatedly observed as common substitutes might be so cheap that the additional monetary gain from substitution outweighs the added risk of detection (Polanco et al. 2012; Wang & Hsieh

2016).

1.7 Labeling regulations

The European Union currently maintains the strictest measures on labeling regulations and tracking of seafood worldwide. The Common Organisation of Markets for fisheries and aquaculture goods was first created in 1970; however, proper labeling and food quality regulations were not established until regulations EC 104/2000, No

2065/2001, and No 178/2002 (EC 2000, 2001, 2002). Among the effects these regulations created the European Food Safety Authority, prohibit the selling of unsafe food, ensured traceability of food products throughout the supply chain, and required that labels include 1) “the commercial designation of the species” 2) “the production method

(caught at sea or inland waters or farmed)” and 3) ‘the catch area.” Regulation (EC)

1224/2009 added further control for seafood product tracking. Regardless of these regulations, they were limited in their enforcement potential as mislabeling rates were still markedly high. Most recently adopted is “Regulation (EU) No 1379/2013 of the

European Parliament and of the Council of 11 December 2013 on the common organization of the markets in fishery and aquaculture products, amending Council

Regulations (EC) No 1184/2006 and (EC) No 1224/2009 and repealing Council

Regulation (EC) No 104/2000” enhanced labeling requirements and (EC 2013). These regulations do not cover products where fish is a minor ingredient or mixed with other fish (Di Pinto et al. 2016). In 2012, the EU responded to the epidemic of mislabeling fraud by implementing the Labelfish® program – “The Atlantic Network on Genetic

Control of Fish and Seafood Labelling and Traceability.” The goal has been to increase traceability, transparency, and labeling within the massive European fishing industry.

Recent evidence indicates these efforts may be having an effect on mislabeling rates

(Bénard-Capelle et al. 2015; Mariani et al. 2016)

Compared to the EU, United States regulations are considerably more ambiguous and non-requisite (Mariani et al. 2015). The European Union also oversees a greater diversity of culture and political groups and thus the lack of regulation within the United

States is unacceptable. Only 2% of imported seafood to the United States was inspected by the FDA (FDA 2008). Rates of mislabeling are typically reflected by the degree to which regulation, oversight, and enforcement is carried out in a nation. This means that mislabeling of seafood products is almost certain to perpetuate indefinitely in nations that maintain ambiguous, unenforced, or even nonexistent laws such as the United States or in many developing countries.

1.8 Spain and Cod

Atlantic cod (G. morhua) is arguably the most historically notable fish in the world due to its persistent presence, popularity, and value to European markets since its discovery by the Basques in the 14th century (Kurlansky 1999). Presently, Atlantic cod remains a valuable, gastronomic staple of Spanish culture. The lack of fat in cod meat

allowed for the fish to be heavily salted, a highly effective form of preservation. Because salted cod meat remains preserved so long, it was able to be brought inland to new markets where other fish could not practically be brought before perishing (Kurlansky

1999). In doing so, cod was often one of, if not the only, source(s) of fish meat available to many communities until better preservation and/or transportation methods developed

Spain has a large economic dependency and cultural attachment to fish. Spain boasts the largest fishing fleet in the European Union in terms of size and tonnage (CBI

2015). Spain was also the ninth largest exporter of fish and fishery products, exporting

3.927 billion dollars. In terms of cod catch however, their contribution is relatively minimal. Spain has been significantly reducing their cod fishing fleet. In 2012, there were five companies in charge of nine fishing vessels specifically targeting cod for an annual revenue (Gonzolez-Lopez 2012).

Despite, little contribution to domestic demand of Atlantic cod by the Spanish cod fleet, the demand and popularity of cod in Spain has remained incredibly high. In order to meet the high demand for cod, Spain imports nearly all of their cod products. In 2012,

Spain remained the fourth largest importer of fish in the world importing 6.4 billion US dollars’ worth of fish (FAO 2014). Spain imports the largest quantity of fresh cod from

Norway, importing approximately 841 million tons in 2014, followed by Iceland

(Forristall 2014).

Spain is also a country shown recently to have high mislabeling rates for fishes and other aquatic species, and shown to be a main contributor to Illegal, Unregulated, and

Undocumented (IUU) fishing throughout Europe. Fishing Secretary Villauriz said control in Spain is expensive because of the “sheer size of its industry – more than 10,000

fishing boats, 2,084 miles of coastline and 47 major ports” (Wilson et al. 2011). As a part of the EU Spain follows the same importation guidelines. The EU inspects approximately 20% of its seafood imports. In a 2015 report by the Centre for the

Promotion of Imports of the European Union, Spain was stated as being the largest seafood importer from developing countries (Figure 2). Fish mislabeling is exacerbated when transparency, enforcement, and tracking are inadequate as is the case in many

Source of European Seafood Imports

€ Million €

Figure 1.1: Source of European country seafood imports. Source: CBI 2015 developing countries. Developing countries have less strict fishing regulations and oversight compared to developed countries meaning that they are more likely to export mislabeled fish, or cheap fish that if substituted for other species could fetch worthwhile profits.

In terms of Spanish cod consumption, 81.5% of cod is eaten in consumer’s home,

17.5% is eaten at hotels and restaurants, and 1% at institutions (Mercasa 2006). The cod that is eaten at home is purchased 41.3% from supermarkets, 10% from hypermarkets,

43% from traditional stores, and 6% from other locations. For the purposes of this thesis,

supermarkets and hypermarkets are grouped together and referred to only as supermarkets. In the 2015, Mercasa report on the distribution and consumption of fish products, Spanish consumers are purchasing more Atlantic cod from supermarkets and hypermarkets now than from traditional stores. This report also states that the value of

Atlantic cod purchased in 2014 was 370.6 million euros with the per capita price per kilo at 1.1. This is a steady rise from 245.6 million euros and a per capita price per kilo of 0.7 from the 2009 report. The 2010 report showed respective values of 295.5 and 0.9. This shows consumption has risen despite increase in price.

CHAPTER 2

HYPOTHESES

2.1 Expected Trends in Mislabeling

It was hypothesized that mislabeling would occur more readily in samples that would be easier to disguise. In particular, samples that were devoid of identifiable parts

(such as the head, fins, skin) and were more processed. This unfortunately refers to most products: frozen, salted, precooked, restaurant, and canned samples. Fresh products, especially larger and skin-on fillets, were expected to have much lower rates of mislabeling. In terms of location purchased, supermarkets and restaurants were hypothesized to have higher rates of mislabeling due to the more processed and cooked products that are sold there.

2.2 Expected Substitutions

The most likely substitutions were hypothesized to be haddock (Melanogrammus aeglefinus), saithe (Pollachius virens), pollock (Pollacius pollachius), and Pacific cod

(Gadus microcephalus). This is due to their prevalence as substitutes in other cod mislabeling research, the similarity in meat color, and their lower costs (Miller & Mariani

2011; Warner et al. 2011). Other white meat fish species were expected to be found as substituted species but in lower quantities than those listed.

CHAPTER 3

MATERIALS AND METHODS

3.1 Sample Collection

Between August and November 2013, I collected a total of 636 commercial fish product samples sold from markets, supermarkets, and restaurants throughout eight

Spanish cities that were labeled unambiguously as Atlantic cod, Gadus morhua, or

‘bacalao’ in Spanish. Sample collection took place in Madrid, Salamanca, Santiago de

Compostela, Bilbao, Barcelona, Valencia, Granada, and Seville (Figure 3.1). These are Sample Collection Route

Figure 3.1: Sample collection route starting in Madrid and ending in Seville. Collection took place between August and November 2013

all populous cities in Spain that are geographically dispersed throughout the country and reflect six major regions (Madrid, Galicia, Basque Country, Catalonia, Comunidad

Valenciana, and Andalucía). Together they provide a spatial and geographic outlook on mislabeling rates throughout the Iberian Peninsula (Table 3.1). Higher quantities of

Table 3.1: Samples Collected by City

# of Collected City Samples Madrid 112 Salamanca 72 Santiago 72 Bilbao 72 Barcelona 92 Valencia 72 Seville 71 Granada 71 Totals 634 Table 3.1: Number of samples collected in each city samples were collected in the latter mentioned cities in order to account for larger population sizes. By taking a large data set, along with duplicates, from different products, throughout eight cities, mislabeling rates could be quantified across a diversity of consumers, from unprocessed fishes to restaurant offerings.

Within each city samples were collected from supermarkets (i.e. traditional grocery stores, hypermarket), markets (i.e. fishmongers, specialized stores), and restaurants (Table 3.2) (Figure 3.2).

Table 3.2: Samples Collected by Location of Purchase

Location # of Collected Purchased Samples Market 192 Supermarket 375 Restaurant 67 Totals 634 Table 3.2: Number of samples collected by location of purchase

Samples were collected within city limits which means there is some sampling bias towards urban centers and against suburban or rural areas. From within those cities though a large quantity and variety of vendors were sampled to ensure representation of near all purchasing options available to consumers. In addition, sampling attempted to reflect the proportion of markets to supermarkets encountered during sampling throughout each city. So cities, particularly Barcelona, where a higher proportion of

Samples Collected by Location of Purchase

67 192

375

Market Supermarket Restaurant

Figure 3.2: Proportion of the total samples collected by their location of purchase fresh markets were found meant more market samples were collected, and cities such as

Santiago de Compostela and Seville where few markets were found meant fewer market

samples were collected. In general, more supermarkets were encountered so most sampling occurred in those locations. The majority of consumers purchase fish from supermarkets (Cerdeño 2012). More samples were collected in general from larger stores, and stores that sold a larger selection of cod products, to avoid unnecessary redundancies in sampling. On average, eight restaurant samples were collected from each city although more were collected from Barcelona (11) and Madrid (13) to account for higher population. Restaurant sampling was much more limited compared to market and supermarket sampling due to the typically high cost of cod dishes at restaurants.

Figure 3.3, on the following page, illustrates the proportions of samples that were sequenced from each city by location purchased. This does not directly reflect the samples collected but instead the samples that were successfully sequenced for barcoding analysis as only those samples affect the mislabeling data for this research.

Products labeled as Atlantic cod in Spain come in a wide variety of product types.

The types of products gathered during sampling were divided into frozen, restaurant, fresh, salted, smoked, precooked, canned, and desalted samples (Table 3.3) (Figure 3.4).

Table 3.3: Sample Collected by Product Type

Product Type # of Collected Table 3.3: SampleData CollectedSamples by Product Type Frozen 179 Restaurant 67 Fresh 95 Salted 173 Smoked 22 Precooked 36 Canned 30 Desalted 21 Liver 11 Totals 634 Table 3.3: Number of samples collected for each product type

Proportion of Samples Sequenced by Location of Purchase for each City

Figure 3.3: Proportions of samples sequenced by location by purchased (market, supermarket, or restaurant) for each city.

Sample Collected by Product Type

21 30 36 22 179

173 67

Frozen Restaurant Fresh Salted Smoked Precooked Canned Desalted Liver Figure 3.4: Proportion of the total samples collected by their product type. Product types were typically sampled in the proportion in which they were found.

Markets typically sold salted and fresh samples; whereas, supermarkets typically sold a wider diversity of product types particularly frozen samples. Fresh samples were typically skin-on fillets. Salted samples were sold in a very large diversity of fish cuts

(lomos, lomito, tacos, colas, migas, rodaja, koktxas).

Precooked samples included samples already cooked such as croquetas and buñuelos, and samples sold at markets or supermarkets ready to eat such as bacalao al pil- pil. Canned cod were huevos de bacalao (cod eggs), bacalao al vizcaina, and bacalao pimientos piquillo. Smoked samples were typically packaged, thinly cut, and skin-off products. Some of the product categories overlap to some degree, for instance some precooked croquetas products were also frozen products and cod liver products were typically canned. Thus, product categorization in particular circumstances is somewhat

arbitrary however products were distinguished into categories that were thought to be the most characteristic.

To preserve and ship samples, cod products were purchased from vendors and were quickly after isolated into a small, sealed polypropylene tubes and preserved in 95% ethanol. Soft tissue samples were extracted carefully and cleanly from each product.

Duplicate samples from each product were gathered to increase the chance of each product yielding clean sequences in case one sample became too degraded to work.

Between tissue extractions, forceps used for tissue extraction were cleaned thoroughly to ensure minimal chance of cross-contamination. In order to ship these samples to the

United States, the ethanol used in each sample had to be poured out. Once samples were received at the University of South Carolina, 95% ethanol was immediately added again to ensure preservation.

Finally, 86 samples were collected from 42 products which contained multiple pieces/cuts/fillets of meat to identify whether meat from different species could be in the same product.

Proportion of Samples Sequenced by Product Type for each City

Figure 3.5: Proportions of samples sequenced by product type for each city.

3.2 DNA Isolation and Sequencing

DNA from each sample was extracted using Qiagen DNeasy blood and tissue

DNA extraction kits following the manufacturers protocol. Small tissue samples

(≤10mg) were placed in 1.5ml microcentrifuge tubes. 180uL ATL buffer was added to the samples followed by 20 ul of proteinase k (>600 mAU/ml). The proteinase k breaks down the tissue’s proteins and cells allowing suspension of the DNA into solution. The solution was vortexed throughout this procedure. The vial was incubated at 56° for at least 30 minutes. AL buffer (200uL) was added followed by 200 ul of 96-100% ethanol.

The total mixture was then pipetted into a special designed flow-through column placed within a 2mL collection tube. The flow-through column has a silica membrane which retains the DNA while allowing other solution to be centrifuged through. The column and collection tube was centrifuged at 8000rpm for one minute. The collection tube was discarded, and another was replaced. 500 ul of AW1 buffer is added to the column.

Centrifuging occured again at 8000pm for 1 minutes. The collection tube was discarded and replaced. 500uL of AW2 buffer was added. Centrifuging occurred again now at

14,000rpm for 3 minutes. The collection tube was discarded. The spin column was placed in a 1.5ml microcentrifuge tube. 200uL Buffer AE was added to the column.

This was centrifuged at 8000rpm for 1 minute. Finally, the spin column was discarded and the extracted DNA was isolated in the microcentrifuge tube. This DNA was stored at

-20°C until amplified through PCR (DNeasy Blood & Tissue Handbook).

A 25uL cocktail of ultrapure water, 10x buffer, MgCl2, dNTP, taq, extracted sample DNA, and forward and reverse loci-specific CO1 primers was created for amplification through PCR. A standard thermocycler protocol was used to amplify DNA

with an annealing temperature between 42-52°C dependent on which temperature provided the highest DNA yields. Gel electrophoresis was then used to determine whether samples successfully amplified. The procedure follows: 100mL of TBE buffer was added to a flask followed by 1.5g of agarose. This flask was microwaved until the agarose had completely dissolved in the TBE. Then, 1uL of ethidium bromide was added to the solution. This solution was poured onto a plate for the solution to solidify. Well combs were placed across the plate. Once the gel solidified well combs were removed and the gel was placed in a horizontal gel electrophoresis system. 5uL of PCR product mixed with 2uL loading dye buffer was added to each well. 7uL of a standard ladder was added to one well in each row to ensure control. The machine was turned on to ~80V for

45 minutes. After, the gel was removed and observed under UV light. Observation of distinct fluorescent bands indicated successful amplification.

Fluorescent base pairs were then added to each successfully amplified product.

This was done by adding a 2uL mixture of EXO-1, SAP, and UPW to 2uL to the PCR product. This was incubated at 37C for 30mintues and 95 for 5 minutes. 1.5uL of this solution was then added to a cocktail of BigDye, 5x Buffer, forward primer, and UPW.

The samples were fully run through the PCR process again to adhere fluorescent base pairs to sequences that allow for detection by machine sequencing.

Samples were subsequently purified through ethanol precipitation. 1uL of sodium acetate and 40uL of 95% ethanol was added to the sample product. The product was centrifuged (1500xg) for 45mintues. The plate was inverted and centrifuged at 300G for

2 minutes. 40uL of 70% ethanol was added. The plate was centrifuged (1500xg) for 10m minutes again, and then inverted and spun at 300g for 2 minutes. The plate was kept at -

20C until it was shipped to Functional Biosciences for sequencing by machine based fluorescent sequencing.

3.3 DNA Barcoding

DNA barcoding was used to identify individual tissue samples. This process used a universal PCR-based assay of the Cytochrome Oxidase-I (COI) locus; primer sequences and PCR conditions are standardized as part of the Fish Barcode of Life (FBOL) initiative. Barcoding uses COI sequences compared to a large COI FBOL sequence database. Statistical analyses were used to assign individual samples to species with a probability assignment. Given genetic identification, individual samples could be confidently assigned to species, thus allowing the estimate of Atlantic cod mislabeling rates across Spain to be derived.

Before sequences were compared to barcoding databases however they were first edited using the program Sequencher. These sequences were then aligned using the program BioEdit. Of the total 418 CO1 sequences, 335 sequences were greater than 600 base pairs (bp) long (typically 636 bp). Due to degradation of DNA however numerous samples provided shorter sequences. Between 500-600bp there were 24 sequences, 39 between 400-500 bp, 16 between 300-400bp, and four less than 300bp long. After editing and aligning, the sequences were compared to both the Barcode of Life Database

(BOLD) and GenBank databases. These programs both use different assignment statistics and compare to different databases. This redundant analysis ensured that each sequence was not assigned to an erroneous species sequence that may have been uploaded into a database. Furthermore, the next closest match for each mislabeled

species assignment was documented (Table 4.10). There is ~.02% intraspecific variation in Atlantic cod (G. morhua) CO1 and a ~2% interspecific variation in CO1 between

Atlantic cod (G. morhua) and its next closest match of Alaskan pollock (G.

Chalcogrammus). Therefore, a threshold cutoff for Atlantic cod sequences at 98% was established. No species besides Gadus morhua were identified above this threshold for samples identified as Gadus morhua.

3.4 Retesting with 16s

Samples that did not amplify with the use of the CO1 locus, or were shown to be mislabeling by CO1 sequencing were retested using 16s. The first reason for this retesting is that collected samples had the potential to have been degraded. Many of the samples collected were highly processed food products, and all samples were shipped without ethanol for a short period to the United States. Thus, the failure to amplify a portion of samples was expected. 16S was shown to work in our lab in many cases where

CO1 would not, and thus after initial CO1 sequencing, 16S was used to increase sequencing yield and substantiate the final dataset to the highest degree. 16s is a much conserved, universal locus that has comprehensive presence in the GenBank barcoding database making it a good locus to use as an alternative or in conjunction with CO1.

The other use of 16S retesting was to validate mislabeling assignments. Samples initially matching mislabeled species were again barcoded using the 16s locus in order to reinforce the validity of the findings, and ensure no errors were made in process of CO1 barcoding. In four mislabeled samples however, only the 16s provided a sequence.

3.5 Geographic Analysis

Geographic analysis of mislabeling rates between cities, and other geographic parameters (such as coastal and inland cities) will be tested by use of chi squared tests of independence and principle component analysis. This will statistically determine whether differences in mislabeling rates are random or related. This chi squared test was also used to determine if differences in mislabeling rates between types of fish products, and if differences between where a product is purchased (markets, supermarket, and restaurant), are random or related. The principle component analysis will compare additional geographic trends with mislabeling such as the population of each city, the distance to a coastline, and distance to the Atlantic coast.

CHAPTER 4

RESULTS

This data reveals a mislabeling rate for Atlantic cod (Gadus morhua) of 6.4%

(35/546) throughout Spain. Of the samples collected there was a high yield rate for successful sequencing of the collected samples at 86.1%. The results presented in this chapter are partitioned into mislabeling by city, mislabeling by product type, mislabeling by location of purchased, relatedness of substituted species, and substituted species data.

All data in the presented tables and figures is compiled from the Appendix Table A which contains data for all collected and sequenced samples including DNA barcoding species assignment statistics. Color scales in all tables correspond to increased values and are used for facilitated interpretation of the data.

4.1 Mislabeling by City

The lowest mislabeling was recorded in Madrid (4.0%) and the highest mislabeling in Seville (11.1%) (Table 4.1). The other six cities maintained a confined range of mislabeling rates between 4.9% and 7.5%. Figure 4.1 represents this data in a visualized map view. Table 4.1: City Summary Data

# of % of # of % of # of % City Collected Collected Sequenced Sequenced Mislabeled Mislabeling Samples TableSamples 4.1: CitySamples Summary DataSamples Samples Madrid 112 17.7% 90 16.5% 3 3.3% Salamanca 72 11.4% 65 11.9% 4 6.2% Santiago 72 11.4% 61 11.2% 3 4.9%

Bilbao 72 11.4% 66 12.1% 5 7.6% Barcelona 92 14.5% 81 14.8% 6 7.4% Valencia 72 11.4% 65 11.9% 4 6.2% Seville 71 11.2% 63 11.5% 7 11.1% Granada 71 11.2% 55 10.1% 3 5.5% Totals 634 100% 546 100% 35 6.4% Table 4.1: Summary of collection, sequencing, and mislabeling data for each city. This data is compiled from table A of the appendix.

4.2 Mislabeling by Product Type

Mislabeling rates as they relate to product type show that restaurant (14.8%), salted (8.2%), precooked (14.7%), and desalted samples (22.2%) had higher than average rates of mislabeling occurrence (Table 4.2). Opposingly, fresh (4.1%), frozen (0.6%), smoked (0%), and canned (0%) samples had lower than average rates of mislabeling. It must be noted that mislabeling data for precooked (31 samples), desalted (20), smoked

(18), and canned (12) samples is limited by low sampling size and is therefore more prone to error. The frozen, restaurant, fresh, and salted categorized products are however substantiated by very high amounts of sampling.

Table 4.2: Product Type Summary Data

# of % of # of % of # of % of Product Collected Collected Sequenced Sequenced Mislabeled Mislabeling Type Data Rate by Samples Samples Samples Samples Samples Product Type Frozen 177 27.9% 167 30.6% 1 0.6% Restaurant 67 10.6% 54 9.9% 8 14.8% Fresh 94 14.8% 73 13.4% 3 4.1% Salted 173 27.3% 171 31.3% 14 8.2% Smoked 22 3.5% 17 3.1% 0 0.0% Precooked 39 6.2% 34 6.2% 5 14.7% Canned 41 6.5% 12 2.2% 0 0.0% Desalted 21 3.3% 18 3.3% 4 22.2% Totals 634 100.0% 546 100.0% 35 6.4% Table 4.2: Summary of collection, sequencing, and mislabeling data by product type. Data compiled from Appendix Table A

Proportion of Mislabeld Samples by City

Figure 4.1: Visualized map view of mislabeling rates by city.

The following tables show the amount of samples sequenced (Table 4.3), amount of samples mislabeling (Table 4.4), and percent of samples mislabeled (Table 4.5) by product type for each city. Certain noticeable correlations between city and mislabeled product types were observed. Mislabeling found in Madrid was entirely attributed to mislabeling in restaurants. Similarly, Granada contained two mislabeled restaurant samples with only three restaurant samples being mislabeled. Finally, mislabeling in

Santiago de Compostela was entirely present in salted or desalted samples.

Table 4.4: Sequenced Samples by Product Type for each City

City Frozen Restaurant Fresh Salted Smoked Precooked Canned Desalted Madrid 34 12 12 21 1 7 2 1 Salamanca 22 7 4 25 0 2 3 2 Santiago 29 2 3 25 0 1 0 1 Bilbao 16 6 17 18 1 3 0 5 Barcelona 21 11 7 34 1 5 0 2 Valencia 13 5 11 19 6 4 3 4 Seville 14 8 10 17 4 5 3 2 Granada 18 3 9 12 4 7 1 1 Totals 167 54 73 171 17 34 12 18 Table 4.3: Number of samples sequenced by product type for each city Table 4.4: Mislabeling by Product Type for each City

City Frozen Restaurant Fresh Salted Smoked Precooked Canned Desalted Madrid 0 3 0 0 0 0 0 0 Salamanca 0 1 0 2 0 0 0 1 Santiago 0 0 0 3 0 0 0 0 Bilbao 0 0 1 0 0 1 0 3 Barcelona 0 1 0 4 0 1 0 0 Valencia 0 1 1 1 0 1 0 0 Seville 1 0 1 4 0 1 0 0 Granada 0 2 0 0 0 1 0 0 Totals 1 8 3 14 0 5 0 4 Table 4.4: Number of samples mislabeled by product type for each city

Table 4.5: Mislabeling Rate by Product Type in each City

City Frozen Restaurant Fresh Salted Smoked Precooked Canned Desalted Madrid 0% 25% 0% 0% 0% 0% 0% 0% Salamanca 0% 14% 0% 8% 0% 0% 0% 50% Santiago 0% 0% 0% 12% 0% 0% 0% 0% Bilbao 0% 0% 6% 0% 0% 33% 0% 60% Barcelona 0% 9% 0% 12% 0% 20% 0% 0% Valencia 0% 20% 9% 5% 0% 25% 0% 0% Seville 7% 0% 10% 24% 0% 20% 0% 0% Granada 0% 67% 0% 0% 0% 14% 0% 0% Totals 7% 135% 25% 61% 0% 113% 0% 110% Table 4.5: Percent of samples mislabeling compared to product types sequences in each city The most commonly mislabeled cod products were palitos de bacalao (cod sticks)

(Figure 4.2), croquetas de bacalao (Figure 4.3), and bacalao desmigado or migas de bacalao (cod crumbs) (Figure 4.4). Palitos de bacalao were mislabeled at a rate of 35%

(5/14). Bacalao desmigado/migas de bacalao were mislabeled at a rate of 17.5% (10/57), and finally 22% (4/18) croquetas or buñuelos products were mislabeled. One product of

Palitos de Bacalao

Figure 4.2: Picture of palitos de bacalao which is a long, rectangular cut of fish meat often salted

Migas de Bacalao

Figure 4.3: Picture of migas de bacalao or salted cod crumbs. These are very small, thin, irregularly shapped cuts of cod meat.

Croquetas de Bacalao

Figure 4.4: Picture of a croqueta de bacalao or a fried ball with filling containing cod meat. bacalao desmigado was also found to have two different species in it, Atlantic cod

(Gadus morhua) and Common Ling (Molva molva). In terms of mislabeling by location of purchase restaurant samples (14.8%) had the highest rate; while both market (5.7%) and supermarket (4.3%) samples mislabeling rates were similar (Table 4.6).

4.3 Mislabeling by Location Purchased

Table 4.6: Location Summary Data

% # of % of # of % of # of Location Mislabeled Collected Collected Sequenced Sequenced Mislabeled Purchased by Samples Samples Samples Samples Samples Location Market 192 30.3% 171 31.3% 11 5.7% Supermarket 375 59.1% 321 58.8% 16 4.3% Restaurant 67 10.6% 54 9.9% 8 14.8% Totals 634 100% 546 100% 35 6.4% Table 4.6: Summary of collection, sequencing, and mislabeling data for by location of purchase The following tables show the amount of samples sequenced (Table 4.3), amount of samples mislabeling (Table 4.4), and percent of samples mislabeled (Table 4.5) by location of purchase for each city. Granada (67%), Madrid (25%), Valencia (20%), and

Salamanca (14%) all had high rates of restaurant mislabeling. Bilbao showed only supermarket mislabeling (14%).

Table 4.7: Samples Sequenced by Location of Purchase in each City

Sequenced Market Supermarket Restaurant Madrid 27 51 12 Salamanca 17 41 7 Santiago 11 48 2 Bilbao 26 34 6 Barcelona 36 34 11 Valencia 25 35 5 Seville 13 42 8 Granada 16 36 3 Totals 171 321 54 Table 4.7: Number of samples sequenced by location of purchase for each city

Table 4.8: Samples Mislabeled by Location of Purchase in each City

Sequenced Market Supermarket Restaurant Madrid 0 0 3

Salamanca 2 1 1 Santiago 1 2 0 Bilbao 0 5 0 Barcelona 3 2 1 Valencia 3 0 1 Seville 2 5 0 Granada 0 1 2 Totals 11 16 8 Table 4.8: Number of samples mislabeled by product type for each city

Table 4.9: Mislabeling Rate by Location of Purchase in each City

Sequenced Market Supermarket Restaurant Madrid 0% 0% 25% Salamanca 12% 2% 14% Santiago 9% 4% 0% Bilbao 0% 15% 0% Barcelona 8% 6% 9% Valencia 12% 0% 20% Seville 15% 12% 0% Granada 0% 3% 67% Totals 6.4% 5.0% 14.8% Table 4.9: Percent of samples mislabeling compared to product types sequences in each city

4.4 Substituted Species Relatedness to Atlantic Cod (Gadus morhua)

There is a strong correlation between the frequency of a species being a substitute in a mislabeled product and the relatedness to the species on the label, in this case

Atlantic cod (G. morhua) (Figure 4.10). The correlation is strong up unto the Genus level. The most common substitutes in this study were other North Atlantic groundfish including common ling (Molva molva), saithe (Pollachius virens), haddock

(Melanogrammus aeglefinus), and Alaskan pollock (Gadus chalcogrammus). Gilt-head bream (Sparus aurata), Nile perch (Nile lates), and Vietnamese catfish (Pangasius hypopthalamus) were the three species outside of the Gadiform order with Nile perch being the most conspicuous substitute due to its distinctly red meat.

Table 4.10: Relatedness of Substituted Species

% Samples % Samples % Samples # of Mislabeled Species within within within Mislabeled TableGenus 4.10: Relatedness ofFamily Substituted SpeciesOrder Common Name Same Same Same Samples Genus Family Order

Atlantic Cod Gadus Gadidae Gadiformes

Pacific Cod 2 Gadus Gadidae Gadiformes 17.14% Alaskan Pollock 4 Gadus Gadidae Gadiformes 51.43% Haddock 5 Melanogrammus Gadidae Gadiformes

Saithe 6 Pollachius Gadidae Gadiformes 88.57%

42 Blue Whiting 1 Micromesistius Gadidae Gadiformes

Common Ling 11 Molva Latidae Gadiformes

European Hake 1 Merluccius Merlucciidae Gadiformes

Rock Grenadier 1 Coryphaenoides Macrouidae Gadiformes

Gilt-head Bream 1 Sparus Sparidae Perciformes Nile Perch 1 Lates Latidae Perciformes Vietnamese Catfish 2 Pangasianodon Pangasiidae Siluriformes Table 4.10: Relatedness of substituted species to Atlantic cod (Gadus morhua) at the order, family, and genus levels of taxonomic identity.

4.5 Mislabeled Sample Data

Table 4.11: Mislabeling Sample Data

scien Location CO1 Next CO1 16S Next Samp C0 16 Commo Scientific Mislabeled Type of tific CO1 16s 16s City Purchase Brand Closest Match Closest le # 1 s n Name Name as product Labe Match Match Match2 Table 4.11: Mislabelingd Sample Data Match 2 Match ling? Gadus Common scrambled 100% chalcogram 99% 32 n y Madrid Ling Molva molva cod restaurant restaurant no (741/741) mus (435/435) bocadillo Pollachius de bacalao 100% Pollachius Pollachius 99.8% 53 y y Madrid Saithe virens y atún restaurant restaurant no 100% (531/531) pollachius 94.88% pollachius (525/531) lomo de No listed Nile Lates bacalao 100% next closest Lates 94.8% 54 y y Madrid Perch niloticus rebozado restaurant restaurant no 99.67% (582/582) match calcarifer (555/585)

43 Gadus

Pacific macrocephal bacalao supermark Super 99% Gadus Gadus 99% 126 y y Salamanca cod us desmigado desalted et Mar yes 100% (990/990) morhua 97.70% morhua (989/989) Common migas de 100% Molva 98.5% 156 y y Salamanca Ling Molva molva bacalao salted market no 99.36% (524/524) dypterygia 91.63% Lota lota (528/536) Common palitos de 99.6% Molva 98.2% 164 y y Salamanca Ling Molva molva bacalao salted market no 99.68% (534/536) dypterygia 92.10% Lota lota (538/548) Gadus Alaskan chalcogram bacalao con 100% Pollachius Pollachius 98.9% 171 y y Salamanca Pollock mus salsa restaurant restaurant no 99.84% (543/543) pollachius 94.77% pollachius (537/543) Melanogram bacalao de Santiago de mus islandia supermark Froito 99.8% Merlangius Arctogadus 97.8% 191* y y Compostela Haddock aeglefinus (migas) salted et mar yes 99.83% (444/445) merlangus 94.19% glacialis (435/445) Melanogram bacalao de Santiago de mus islandia supermark Froito 100% Merlangius Arctogadus 98.3% 192* y y Compostela Haddock aeglefinus (migas) salted et mar yes 99.83% (543/543) merlangus 94.19% glacialis (534/543)

Rock bacalao Santiago de Grenadie Coryphaenoi (small 99% Albatrossia 97% 234 n y Compostela r des rupestris strips) salted market no (874/874) pectoralis (813/813) Melanogram filete de mus bacalao supermark 100% Merlangius Arctogadus 98.3% 259 y y Bilbao Haddock aeglefinus fresco fresh et yes 99.67% (543/543) merlangus 93.85% glacialis (534/543) Melanogram mus bolitas de supermark Fridera 91% Arctogadus 90% 306 n y Bilbao Haddock aeglefinus bacalao precooked et r yes (616/616) glacialis (593/593) palitos de Common bacalao supermark 100% Molva 100% 308 y y Bilbao Ling Molva molva rebozados desalted et alkorta yes 99.58% (502/502) dypterygia 89.77% Lota lota (502/502) Common palitos de supermark 99.8% Molva 98.4% 323* y y Bilbao Ling Molva molva bacalao desalted et alkorta yes 99.68% (546/547) dypterygia 92.10% Lota lota (550/559) Common palitos de supermark 100% Molva 98.5% 324* y y Bilbao Ling Molva molva bacalao desalted et alkorta yes 99.68% (536/536) dypterygia 92.10% Lota lota (540/548)

44 Common bacalao 99.4% Molva 98.5% 328 y y Barcelona Ling Molva molva (square cut) salted market no 99.84% (492/495) dypterygia 92.10% Lota lota (488/495) Common bacalao 100% Molva 98.5% 342 y y Barcelona Ling Molva molva (square cut) salted market no 100% (531/531) dypterygia 92.10% Lota lota (535/543) Common bacalao supermark 99% Molva 97% 349 y y Barcelona Ling Molva molva desmigado salted et Dimar yes 100% (957/957) dypterygia 90.89% Lota lota 931/931) Pollachius croquetas 100% Pollachius Pollachius 98.8% 355 y y Barcelona Saithe virens de bacalao restaurant restaurant no 98.01% (507/507) pollachius 92.05% pollachius (501/507) Pollachius bacalao 100% Pollachius Pollachius 98.9% 361 y y Barcelona Saithe virens tratufas precooked market no 99.84% (543/543) pollachius 94.86% pollachius (537/543) Gadus Pacific macrocephal migas de supermark UBAG 100% Gadus Gadus 99% 411 y y Barcelona cod us bacalao salted et O 99.84% (992/992) morhua 98.06% morhua (985/985) Gadus 100% Theragra 100% Alaskan chalcogram migas de (1013/10 Arctogadus finnmarchic (1013/10 425 y y Valencia Pollock mus bacalao salted market no 99.83% 13) glacialis 99.31% a 13)

No listed European Merluccius 99.5% next closest Merluccius 98.5% 433 y y Valencia Hake merluccius bacalao fresh market no 100% (555/558) match capensis (551/559) Gadus Theragra Alaskan chalcogram croquetas Valeas 100% Arctogadus finnmarchic 100% 446 y y Valencia Pollock mus de bacalao frozen market Carnes no 100% (548/548) glacialis 99.84% a (548/548) Pollachius bacalao a 100% Pollachius Pollachius 98.9% 469 y y Valencia Saithe virens lal llauna fresh market no 99.84% (543/543) pollachius 94.87% pollachius (537/543) Common bacalao supermark 100% Molva 98.5% 515* y y Seville Ling Molva molva desmigado salted et MAS no 99.52% (541/541) dypterygia 91.94% Lota lota (545/553) Common bacalao supermark 100% Molva 99% 516* y y Seville Ling Molva molva desmigado salted et MAS no 99.52% (985/985) dypterygia 91.94% Lota lota (965/965) Gilt- Head Sparus filete de 89% Rhabdosargu Rhabdosarg 86% 526 y y Seville Bream aurata bacalao fresh market no 98.94% (760/760) s globiceps 89.79% us globiceps (686/686) Pangasiano 45 Vietname don se hypophthalm palito de supermark Supers 548 Pangasius Pangasius 99.6% 530 y y Seville Catfish us bacalao frozen et ol no 98.52% (99.6%) bocourti 98.39% sutchi (538/540) Gadus 99% Theragra 99% Theragra Alaskan chalcogram bacalao supermark Supers (987/98 99.8% finnmarchic (987/98 finnmarchic 99.8% 535 y y Seville Pollock mus desmigado salted et ol no 7) (543/544) a 7) a (543/544) Melanogram mus bacalao supermark Carref 100% Merlangius Arctogadus 98.3% 543 y y Seville Haddock aeglefinus salado salted et our yes 99.65% (543/543) merlangus 93.77% glacialis (534/543) Pollachius banuelos de supermark Fripoz 100% Pollachius Pollachius 98.9% 557 y y Seville Saithe virens bacalao precooked et o no 99.83% (543/543) pollachius 94.68% pollachius (537/543) Pangasiano Vietname don se hypophthalm bacalao 100% Pangasius 98% 594 n y Granada Catfish us revuelta restaurant restaurant no (872/872) sutchi (857/857) El Pollachius croquetas supermark Corte 99.8% Pollachius Pollachius 98.7% 617 y y Granada Saithe virens de bacalao precooked et Ingles no 99.84% (543/544) pollachius 94.76% pollachius (537/544)

Micromesist Micromesist Blue ius bacalao con 100% uius Gadus 100% 629 y y Granada Whiting poutassou pan restaurant restaurant no 100% (985/985) australis 98.25% morhua (985/985) Table 4.11: Data related to all mislabeled samples genetically identified. * signifies that two adjacent samples were from the same product.

CHAPTER 5

DISCUSSION

These results reveal an overall mislabeling rate of 6.4%. In relation to mislabeling averaged across other research, this is a comparatively low rate. This data corroborates other recent studies illustrating lowering mislabeling rates throughout

Europe. A mislabeling rate of 4.3% across multiple species in western European countries was revealed in 2015 in one of the largest mislabeling studies to date (Mariani et al. 2015). Their overall mislabeling rate for Spain was 8.9% with a mislabeling rate of cod of 3.5% throughout Europe. An overall mislabeling rate of only 3.7% was found in

France (Bénard-Capelle et al. 2015). This reduction has been attributed to increased public awareness, new European Union tracking laws (EC 2013), and the general awareness by businesses that their fraud is no longer an imperceptible act. The most common substitutes in this study were other North Atlantic groundfish within the order

Gadiformes. By far the most frequent substitute was common ling (Molva molva), followed by saithe (Pollachius virens) and haddock (Melanogrammus aeglefinus). The most conspicuous substitutes were Nile perch (Niles lates) and Vietnamese catfish

(Pangasius hypopthalmus). We suspect the majority of mislabeling cases were mislabeled due to the correlation of mislabeling cases with easily disguisable and cheaper substitutes. However, the point along the supply chain at which mislabeling occurred cannot be known. No geographic patterns could be statistically interpreted from the data.

Mislabeling was found to occur in all cities however demonstrated that mislabeling remains a widespread and pervasive issue.

5.1 Characteristics of Spanish Cod mislabeling

It is suspected that the majority of mislabeling in this study was intentional due to the general presence of cheaper substitutes being mislabeled as cod and the prevalence of mislabeling in easily disguised food products. Products (28 out of 35) were demonstrably cheaper products than the cod they were mislabeled as. Table 5.1 shows the monetary gain of mislabeling the haddock (Melanogrammus aeglefinus), Alaskan pollock (Gadus chalcogrammus), and Vietnamese catfish (Pangasius hypophthalmus). In the cases of the

Nile perch (Lates niloticus) and gilt-head bream (Sparus aurata) mislabeling there would have been a monetary loss according to this report. Although the prices of saithe

(Pollachius virens) and common ling are not listed on this report, the presence of other groundfish in cod catches, including saithe (Pollachius virens) and common ling (Molva molva), significantly reduce the value of cod landings (Asche et al. 2015). This further supports the fact that a monetary incentive was present for purposes of mislabeling.

Compounding the possible incentive for financial gain is that the stark national popularity of cod means substitiuting less popular fish species as Atlantic cod would likely mean those fish would sell more readily.

Table 5.1: Mislabeling Sample Data

Price compared to Product Price per kg Fish Species cod Table 5.1:form Mislabeling Sample Data Eur USD Eur USD € $ Cod (Gadus morhua) Fillet 3.95 5.33

Common Ling (Molva molva) N/A N/A N/A N/A

Saithe (Pollachius Virens) N/A N/A N/A N/A Haddock (Melanogrammus Headed € $ aeglefinus) and gutted 2.10 2.83 1.85 2.50 Alaskan Pollock (Gadus € $ chalcogrammus) Fillet 2.52 3.23 1.43 2.10 Rock grenadier (Sparus aurata) N/A N/A N/A N/A

Vietnamese Catfish € $ (Pangasianodon hypophthalmus) Fillet 1.52 2.05 2.43 3.28 Blue Whiting (Micromesistius poutassou) N/A N/A N/A N/A Nile Perch (Lates € $ niloticus) Fresh fillet 4.25 5.63 -0.30 -0.30 Pacific cod (Gadus macrocephalus) N/A N/A N/A N/A Gilt-Head Bream (Sparus Whole € $ aurata) farmed 4.42 5.85 -0.47 -0.52 Table 5.1: Price data based on the FAO European Fish Price Reports from September and October 2013. Regardless of the arguments presented, it cannot be definitively known what occurred, and unintentional mislabeling is certainly a possibility. For other white meat fish that were major substitutes, once filleted even persons handling fish on a day-to-day basis could make mistakes and misidentify the products. Moreover, haddock, saithe, and common ling are North Atlantic groundfish that are often caught while fishing for cod. It is possible that their bycatch could go unnoticed and was landed all under the label of cod

– common ling however does look noticeable different. Even if mislabeling is unintentional though, it is unacceptable for businesses especially if they be large scale processors or fishing vessels to allow this to occur.

Logically, one would expect that those who are trying to hide something, in this case those deliberately mislabeling their fish, to act in a surreptitious manner in order to

minimize chances of detection by mislabeling products that are very difficult to identify.

The most commonly mislabeled products were palitos de bacalao, croquetas or buñuelos de bacalao (small rectangular cuts of salted cod meat), and migas de bacalao or bacalao desmigado (cod crumbs). All three of these products types contain no identifiable parts apart from meat color. The croquetas especially are fried balls with tiny pieces of fish meat mixed with many other ingredients. Most of the bacalao desmigado or migas de bacalao were also covered in a layer of salt. The products are markedly difficult products to identify as cod without genetic analysis. Other mislabeled products include small, salted, square cuts of cod, two cod fillets, and a number of restaurant and precooked samples. The salted square and two fillets could also be easily disguised. The fillets were most likely skin-on; however, those samples were replaced by other white meat fish and would have still been difficult for any consumer to distinguish.

Restaurant as well as many precooked samples, as discussed in Chapter 1, are particularly easy to disguise because the fish meat is often covered in a sauce or mixed with other ingredients that hide the look and/or taste of the fish. This is consistent with other research which show that restaurant samples are more often mislabeled than other products (Pardo et al. 2016). In addition, restaurant dishes are often more expensive than other supermarket or market products making the economic incentive to mislabel higher.

This research extracted multiple samples from certain products and found that two contained more than one species inside (Atlantic cod and Haddock; Atlantic cod and

Common Ling). This case could indicate that common ling meat was accidentally mixed with cod meat. Once morphologically devoid similarly cut pieces of meat are mixed together, it would be extremely hard to distinguish them apart. By mixing the meat of

two closely related species such as Atlantic cod and common ling, it makes disguising the substituted species even more difficult to detect.

5.2 Substituted Species

The majority of substituted fish (32/35) were other Gadiformes. It was hypothesized that the majority of substituted species would be haddock, pollock, saithe, and Pacific cod. All of these species were found expect for the European pollock. Thus, the hypothesis was largely supported. The presence of common ling was not predicted but was neither surprising due to it being a white meat Gadiform. The quantity of their substitutions was surprising however, as this species has not been shown to be a substitute in other cod mislabeling research. Again, the reason for the mislabeling of these fish is most likely financial. The ability to replace Atlantic cod products with other

Gadiformes, especially those fished in the North Atlantic, would likely be very easy as those fish are most likely processed along similar supply lines. This also means there are more nodes along the supply chain at which this switch may occur. The presence of other Gadiformes labeled as cod is fortunately not dangerous to the consumer, but the consumer is regardless not receiving what they paid for, and the product may be of lower quality, or simply not suit their desired palate. The frequent presence of these other species as cod may be due to quota limitations implemented on cod catches.

The presence of Pacific cod in a product with the scientific label of Gadus morhua shows imported fish from distant fisheries are also being substituted for cod.

Pacific cod is very commonly substituted for Atlantic cod in North America due to its cheaper price (Wong & Hanner 2008).

Gilt-head bream is not a closely related species to cod, but it does contain similar white meat. The value of gilt-head bream is shown to be higher than that of cod meaning this case may represent an instance of unintentional substitution.

The mislabeling of Nile perch as cod was the most unexpected discovery due to the fact this fish has noticeable red meat. It is logical that the product was mislabeled in a restaurant sample in a dish where the pieces of fish were finely chopped and could be easily disguised. Nile perch is a cheaper fish than cod however, and was found to be a substitute of 34 grouper products in Spain (Asensio et al. 2009). This shows the substitution of certain species such as this is not limited to specific fish species or products.

The presence of veitnamese catfish in cod samples is not surprising as this species has been found as a substitute in a number of other studies (Galal-Khallaf et al. 2014;

Pappalardo & Ferrito 2015; Polanco 2012). Veitnamese catfish is an abundant freshwater fish from the Mekong river in Southeast Asia. Aquaculture of this species has expanded significantly in the past decade and the fish has since flooded markets globally (Phuong

& Oanh 2010). Its inexpensive price makes it a profitable species to mislabel.

Furthermore, there is a very small market for this fish internationally meaning that marketing it as other species would likely increase sales. It is unlikely that this species could easily be mislabeled by accident as the supply chains involved in its processing and sale would be considerably different than the supply chains of North Atlantic caught groundfish.

5.3 Geographic Analysis

This study identified no statistically clear geographic trends in mislabeling, but rather found very similar rates of mislabeling across all sampled cities. This attests to the ubiquity of mislabeling over geographic regions.

Mislabeling of cod does vary transnationally (Bréchon et al. 2016). A study analyzed North Atlantic countries, both cod producing and cod importing, as well as EU and non EU countries (Canada, Estonia, United Kingdom, Norway, Sweden, and

Iceland). Although variable rates of mislabeling were observed, these was not consistent to whether the countries were cod producing, cod importing, EU or non EU countries

Estonia (59.4%) and Denmark (18.6%) had high rates of mislabeling. Iceland and

Norway showed no mislabeling. This study represents the largest scope in Atlantic cod mislabeling research as far as geographic comparison is concerned; however, it is hampered by limited sampling size (~41 per city) and representation. Samples were only taken from large supermarkets generally from one large city.

5.4 Who is at fault?

It is difficult to pinpoint where in the supply chain, from the initial catch to consumer purchase, at which mislabeling occurred. This has been an issue in other mislabeling research as well (Cline 2012). A considerable amount of megrim in Spain were mislabeled at landing (Crego-Prieto 2012). However, due to the small Spanish cod fishing fleet the majority of Spanish cod is imported, primarily from Norway. It was hypothesized that major exporting countries such as Norway and Iceland may have less economic incentive to mislabel due to the prosperous cod industry as opposed to

countries with less profitable industries (Bréchon et al. 2016). Also, additional supply chain steps may be added by those exports, that are potentially less regulated, making substitution easier (Bréchon et al. 2016). Munoz-Colmenero et al. (2016) found higher mislabeling in wholesale supplier suggesting that mislabeling is more prominent at earlier points in the supply chain; however, this result was hampered by low sampling size.

In this study, despite the comprehensive sampling across Spain, few clear, repeat mislabeling offenders were uncovered. It was found that all three Alkorta brand samples of palitos de bacalao where in fact Common Ling (Molva molva). Supersol also had two different mislabeled products with different substitutes. Besides these a diversity of different brands (Supersol, MAS, Valeas Carnes, Fripozo, El Corte Ingles, UBAGO,

Froitomar, Super Mar) had only one sample mislabeled.

5.5 Broader context

Although this research is focused on Spain, countries throughout the EU attribute similar value and culture popularity to Atlantic cod. For example, cod is more popular and is consumed more per capita in Portugal than any other country (Almeida et al.

2015). This makes the value, ability to sell, and therefore the economic incentive to mislabel Atlantic cod similar across most European countries. Also, most western

European countries import seafood from similar sources. Most of the cod in western

Europe is imported from Norway and Iceland. This means that if mislabeling is occurring before products are exported, then similar mislabeling would affect all countries importing those goods in a similar manner. Mislabeling is not difficult to accomplish and there is little that makes the manner in which cod is mislabeled different

than other species. Thus, the findings of this research likely reflect to at least some extent the mislabeling of other species. The correlation that a substituted species in a mislabeled product is likely to be more taxonomically related to the labeled species likely holds up across other mislabeled species. This research also adds the list of research which attests to the likely deliberate manner in which mislabeling of seafood occurs.

Finally, apart from egregious cases of mislabeling, as the geographic data of this study show, mislabeling is likely similar in occurrence throughout Spain.

CHAPTER 6

CONCLUSION

This intensive, single-species analysis of Atlantic cod (Gadus morhua) mislabeling advances our understanding of seafood fraud in Europe. Because this research was focused, it was able to highlight characteristic trends in Spanish cod mislabeling. 1) Restaurant, salted, desalted, and precooked products were the most frequency mislabeling product types; whereas, frozen and smoked fish products had very little to no occurrences of mislabeling. 2) Apart from restaurants (where mislabeling is high), the location of purchase, whether at a market or supermarket had little influence on whether a product would be mislabeled. 3) The majority of products that were mislabeling were most likely purposefully so as most substituted species were cheaper, and most mislabeling products were particularly disguisable such as migas de bacalao

(cod crumbs). 4) Atlantic cod products were most commonly substituted with other closely related species, particularly North Atlantic groundfish. Nile perch and pangsius catfish, found as substitutes in other research, were again identified in this study showing these to be common substitutes across species. Fortunately, no toxic fish were revealed as substitutes, but consumers are nonetheless largely receiving cheaper, lower quality and/or undesired products. 5) Mislabeling is a widespread, rather than localized, problem. Despite certain trends, detection of mislabeling in all tested cities, among numerous vendors and brand name products, and from a variety of product types shows

mislabeling is a generalized issue. Because it is so easily accomplished, it is likely perpetrated independently by many persons and businesses.

The total 6.4% rate of mislabeling highlights a recent, decreasing trend in mislabeling occurrence. However, 6.4% mislabeling is still an unacceptable high rate of occurrence, one that is only comparatively low because of the egregiously high mislabeling found in other studies. Accordingly, this research adds to collective appeal by consumers, scientists, and policy makers for increased transparency and traceability in the seafood industry. These samples were however gathered just before the most recent

EU 1379/2013 traceability laws were updated, hopefully meaning improvements have already been made. Recent developments in rapid species identification technology, specifically real-time PCR (Herrero et al. 2010), also bodes well for enforcement purposes in the future. More can certainly be done to address such a ubiquitous issue though. Increasing public awareness should be a key initiative here, as this can have direct impacts on mislabeling rates (Mariani et al. 2014). In addition, mislabeling will likely always be prevalent to some degree, but if consumers are aware to be suspicious of what they are buying, and are knowledgeable about what species and products are best to purchase, then they can easily minimize their chances of being victimized by seafood fraud. Groundwork mislabeling research is often the first step towards affecting public awareness. Unfortunately, the quantity of research on mislabeling remains insufficiently small, many countries and commercial species have not yet been investigated, and often research that is done is hampered by small datasets. Regardless, this field of investigatory research is still new as DNA barcoding only became on standardized in

2003, and the quantity of mislabeling research is becoming more comprehensive every

year. It is clear that this research is impactful and it has pushed policy-makers in many countries down the right track. Continued and persistent work is needed to reign in the ability for businesses to get away with seafood fraud, but it is a worthwhile goal that protects consumer rights and health, strengthens the economy, and shuts down major avenues by which IUU fishing can profit.

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APPENDIX A: COMPLETE SAMPLE DATA

Table A.1: Complete Sample Data

Scienti CO1 Date Location fic BOL 16S Samp Produc name Sequence CO1 / Collect City Product Purchase Brand Identified as D BLAST le # t Type on d? 16S ed d packag Matc Match e? h

canned foie supermar 1 8/15 Madrid (cod liver) canned ket no no supermar 2 8/15 Madrid canned foie canned ket officer no no bacalao restaura Table3 A.1:8/15 Complete Madrid Sample portu Dataguesa nt restaurant no no filete de bacalao supermar 4 8/15 Madrid (cod filete) frozen ket día no yes CO1 G. morhua 100% filete de supermar 5 8/15 Madrid bacalao frozen ket día no yes CO1 G. morhua 100%

filete de supermar 6 8/15 Madrid bacalao frozen ket día no

filete de supermar 7 8/15 Madrid bacalao frozen ket día yes yes CO1 G. morhua 100%

lomos de supermar 99.84 8 8/15 Madrid bacalao frozen ket día yes yes CO1 G. morhua % lomos de supermar CO1/1 99.8% 9 8/15 Madrid bacalao frozen ket día yes yes 6S G. morhua 100% (541/542) lomos de supermar 10 8/15 Madrid bacalao frozen ket día yes yes CO1 G. morhua 100% lomos de supermar 99.8% 11 8/15 Madrid bacalao frozen ket día yes yes 16S G. morhua (506/507) porciones supermar 99.83 12 8/15 Madrid de bacalao frozen ket día yes yes CO1 G. morhua % porciones supermar 13 8/15 Madrid de bacalao frozen ket día yes yes CO1 G. morhua 100% ensalada con bacalao 70 horneado y restaura 100%

14 8/15 Madrid salmon nt restaurant no yes 16S G. morhua (507/507) la casa bacalao de 99.84 15 8/16 Madrid foie canned market bacalao yes yes CO1 G. morhua % bacalao CO1/1 99.81 100% 16 8/16 Madrid torneado fresh market yes yes 6S G. morhua % (507/507) bacalao al 99.84 17 8/16 Madrid pil pil fresh market yes yes CO1 G. morhua %

16 8/16 Madrid bacalao fresh market yes no bacalao 19 8/16 Madrid tarajadas fresh market yes yes CO1 G. morhua 100%

20 8/16 Madrid canned foie canned market yes no

migas de bacalao ("cod supermar pescano 21 8/16 Madrid crumbs") frozen ket va yes yes CO1 G. morhua 100% migas de supermar pescano 22 8/16 Madrid bacalao frozen ket va yes yes CO1 G. morhua 100% migas de supermar pescano 23 8/16 Madrid bacalao frozen ket va yes yes CO1 G. morhua 100% migas de supermar pescano 24 8/16 Madrid bacalao frozen ket va yes yes CO1 G. morhua 100% lomos de supermar pescano 25 8/16 Madrid bacalao frozen ket va yes yes CO1 G. morhua 100% bacalao restaura 26 8/16 Madrid frito nt restaurant no yes CO1 G. morhua 100%

71 bacalao salado (desmigado supermar 27 8/16 Madrid ) frozen ket no yes CO1 G. morhua 100% bacalao salado (desmigado supermar 28 8/16 Madrid ) frozen ket no no bacalao supermar carrefou 29 8/16 Madrid desmigado frozen ket r no yes CO1 G. morhua 100% bacalao supermar carrefou CO1/1 100% 30 8/16 Madrid desmigado frozen ket r yes yes 6S G. morhua 100% (542/542) bacalao ahumado (smoked restaura 31 8/16 Madrid cod) nt restaurant no yes CO1 G. morhua 100%

bacalao revuelto (scrambled restaura 100% 32 8/16 Madrid cod) nt restaurant no yes 16S Molva molva (741/741) bacalao horneado restaura 33 8/16 Madrid (baked cod) nt restaurant no yes CO1 G. morhua 100% bacalao 34 8/17 Madrid confitado salted market yes yes CO1 G. morhua 100% callos de 35 8/17 Madrid bacalao salted market yes yes CO1 G. morhua 100% colitas de 36 8/17 Madrid bacalao salted market yes yes CO1 G. morhua 100% carrilleras

72 37 8/17 Madrid de bacalao salted market yes yes CO1 G. morhua 100%

cocochas 38 8/17 Madrid de bacalao salted market yes yes CO1 G. morhua 100% medias 39 8/17 Madrid bacalao salted market yes yes CO1 G. morhua 100% supermar carrefou 40 8/17 Madrid bacalao frozen ket r yes no supermar carrefou 41 8/17 Madrid bacalao frozen ket r yes yes CO1 G. morhua 100% filete de supermar pescano 42 8/17 Madrid bacalao frozen ket va yes yes CO1 G. morhua 100% desmigado de bacalao supermar 99.84 43 8/17 Madrid desalado salted ket royal yes yes CO1 G. morhua %

desmigado (tira de lomo de supermar 99.84 44 8/17 Madrid bacalao) salted ket royal yes yes CO1 G. morhua % lomos selectos de supermar 45 8/17 Madrid bacalao salted ket royal yes yes CO1 G. morhua 100% lomos de supermar 46 8/17 Madrid bacalao fresh ket scanfisk no no bacalao ahumado con aceita supermar cadelma 47 8/17 Madrid de oliva smoked ket r no yes CO1 G. morhua 100% filetes de bacalao supermar 48 8/17 Madrid desalado desalted ket royal yes yes CO1 G. morhua 100%

bacalao al supermar cadelma 49 8/17 Madrid pil pil fresh ket r no yes CO1 G. morhua 100% bacalao al supermar cadelma 50 8/17 Madrid pil pil fresh ket r no yes CO1 G. morhua 100% bacalao restaura 100% 51 8/17 Madrid vizcaina nt restaurant no yes 16S G. morhua (507/507) bacalao dorado ("golden restaura 100% 52 8/18 Madrid cod") nt restaurant no yes 16S G. morhua (407/407) bocadillo de bacalao restaura CO1/1 Pollachius 100% 53 8/18 Madrid y atún nt restaurant no yes 6S virens 100% (531/531) lomo de bacalao restaura CO1/1 Lates 99.67 100% 54 8/18 Madrid rebozado nt restaurant no yes 6S niloticus % (582/582)

bacalao 99.68 55 8/19 Madrid brandada fresh market yes yes CO1 G. morhua % bacalao marinado 56 8/19 Madrid con aceite fresh market yes no bacalao 99.84 57 8/19 Madrid horneado fresh market yes yes CO1 G. morhua % cocochas 58 8/19 Madrid de bacalao salted market yes yes CO1 G. morhua 100% bacalao 99.84 59 8/19 Madrid horneado fresh market yes yes CO1 G. morhua % ajohierro 60 8/19 Madrid bacalao fresh market yes yes CO1 G. morhua 100% cocochas 74 61 8/19 Madrid de bacalao fresh market yes no

cocochas 62 8/19 Madrid de bacalao salted market yes yes CO1 G. morhua 100% lomo de bacalao 100% 63 8/19 Madrid rebozado salted market yes yes 16S G. morhua (507/507) tajada de bacalao (slice of 64 8/19 Madrid cod) salted market yes yes CO1 G. morhua 100% medias 65 8/19 Madrid bacalao salted market yes yes CO1 G. morhua 100% desmigado 66 8/19 Madrid fino salted market yes yes CO1 G. morhua 100%

bacalao 67 8/19 Madrid laminado salted market yes yes CO1 G. morhua 100% la casa foie de de CO1/1 99.10 99.1% 68 8/19 Madrid bacalao canned market bacalao yes yes 6S G. morhua % (444/448) bacalao 69 8/19 Madrid laminada salted market yes yes CO1 G. morhua 100% bacalao 70 8/19 Madrid callos salted market yes yes CO1 G. morhua 100% tacos de supermar 71 8/19 Madrid bacalao frozen ket none no yes CO1 G. morhua 100% tacos de supermar 99.84 72 8/19 Madrid bacalao frozen ket none no yes CO1 G. morhua % filetes de supermar 75 73 8/19 Madrid bacalao frozen ket findus yes no

filete de supermar 74 8/19 Madrid bacalao frozen ket findus yes no filetes de supermar 75 8/19 Madrid bacalao frozen ket findus yes yes CO1 G. morhua 100% filetes de supermar 76 8/19 Madrid bacalao frozen ket findus yes no palito de bacalao supermar carrefou 99.8% 77 8/19 Madrid salado frozen ket r yes yes 16S G. morhua (552/553) palito de bacalao supermar carrefou 78 8/19 Madrid salado frozen ket r no yes CO1 G. morhua 100% palito de bacalao supermar carrefou 79 8/19 Madrid salado frozen ket r no yes CO1 G. morhua 100%

palito de bacalao supermar carrefou 80 8/19 Madrid salado frozen ket r no yes CO1 G. morhua 100% bacalao salado supermar seccion 81 8/19 Madrid tradicional frozen ket dimar yes yes CO1 G. morhua 100% recetas croquetas precook supermar artesana 98.80 82 8/19 Madrid de bacalao ed ket s yes yes CO1 G. morhua % recetas croquetas precook supermar artesana 83 8/19 Madrid de bacalao ed ket s yes no huevas de supermar 84 8/19 Madrid bacalao canned ket UBAGO no no huevas de supermar

76 85 8/19 Madrid bacalao canned ket UBAGO no no huevas de supermar 86 8/19 Madrid bacalao canned ket UBAGO no no croquetas precook supermar 87 8/19 Madrid de bacalao ed ket no yes CO1 G. morhua 100% bacalao con gambas y olivos restaura 88 8/20 Madrid negros nt restaurant no yes CO1 G. morhua 100% tacos de bacalao con un punto de supermar 89 8/20 Madrid sal frozen ket la sirena yes no buñuelos supermar 90 8/20 Madrid de bacalao frozen ket la sirena yes yes CO1 G. morhua 100%

bacalao de supermar 99.84 91 8/20 Madrid islandia frozen ket la sirena yes yes CO1 G. morhua % croquetas precook supermar 92 8/20 Madrid de bacalao ed ket la sirena no yes CO1 G. morhua 100% croquetas de brandada precook supermar premiu 93 8/20 Madrid de bacalao ed ket m no yes CO1 G. morhua 100% mini croquetas precook supermar 94 8/20 Madrid de bacalao ed ket la sirena no yes CO1 G. morhua 100% pimientos del piquillo rellenos de precook supermar 100% 95 8/20 Madrid bacalao ed ket la sirena no yes 16S G. morhua (492/492) 77 lomo de supermar 96 8/20 Madrid bacalao frozen ket la sirena yes yes CO1 G. morhua 100% lomo de supermar 97 8/20 Madrid bacalao frozen ket la sirena yes yes CO1 G. morhua 100% lomo selecto de supermar premiu 98 8/20 Madrid bacalao frozen ket m yes yes CO1 G. morhua 100% penca bacalao supermar 99 8/20 Madrid desalado frozen ket la sirena yes yes CO1 G. morhua 100% bacalao (a punto de supermar 100 8/20 Madrid sal) frozen ket la sirena yes yes CO1 G. morhua 100% tortilla de restaura 100% 101 8/20 Madrid bacalao nt restaurant no yes 16S G. morhua (507/507)

filete de 99.79 102 8/21 Madrid bacalao fresh market no yes CO1 G. morhua % filete de 103 8/21 Madrid bacalao fresh market no no lomo de 104 8/21 Madrid bacalao fresh market no no migas de 105 8/21 Madrid bacalao fresh market no no traceado de 106 8/21 Madrid bacalao fresh market no no bacalao supermar bacalao 107 8/21 Madrid desmigado salted ket pleamar yes yes CO1 G. morhua 100% lomo supermar fan di

78 108 8/21 Madrid bacalao salted ket costa yes yes CO1 G. morhua 100% porciones supermar alipende 109 8/21 Madrid de bacalao salted ket r yes yes CO1 G. morhua 100% filete de 99.83 110 8/21 Madrid bacalao fresh market no yes CO1 G. morhua % filete de 111 8/21 Madrid bacalao fresh market no no bacalao restaura 112 8/21 Madrid dorado nt restaurant no yes CO1 G. morhua 100% bacalao con salsa de Salaman perejil y restaura 113 8/22 ca patatas nt restaurant no yes CO1 G. morhua 100% Salaman restaura 99.84 114 8/22 ca bacalao nt restaurant no yes CO1 G. morhua %

Salaman croquetas restaura 115 8/22 ca de bacalao nt restaurant no no Salaman filete de supermar 99.5 116 8/22 ca bacalao fresh ket no yes CO1 G. morhua % Salaman desmigado supermar 100% 117 8/22 ca de bacalao salted ket royal yes yes 16S G. morhua (507/507) Salaman tacos de supermar carrefou 99.84 118 8/22 ca bacalao desalted ket r yes yes CO1 G. morhua % Salaman filete de supermar carrefou 119 8/22 ca bacalao fresh ket r no yes CO1 G. morhua 100% Salaman filete de supermar carrefou 99.70 120 8/22 ca bacalao fresh ket r no yes CO1 G. morhua % bacalao Salaman salado supermar carrefou 79 121 8/22 ca filetón salted ket r yes no

Salaman lomo de supermar carrefou 122 8/22 ca bacalao frozen ket r yes yes CO1 G. morhua 99% Salaman restaura 123 8/23 ca bacalao nt restaurant no yes CO1 G. morhua 100% pimientos del piquillo el Salaman rellenos de supermar navarric 124 8/23 ca bacalao canned ket o no no Salaman lomo oro supermar super 125 8/23 ca de bacalao salted ket mar yes yes CO1 G. morhua 100% Gadus Salaman bacalao supermar super CO1/1 macrocephalu 99% 126 8/23 ca desmigado desalted ket mar yes yes 6S s 100% (990/990) Salaman higado de supermar 127 8/23 ca bacalao canned ket officer no no

Salaman filete de supermar 128 8/23 ca bacalao frozen ket dimar yes yes CO1 G. morhua 100% Salaman bacalao supermar 129 8/23 ca troceado frozen ket dimar yes yes CO1 G. morhua 100% Salaman bacalao supermar 130 8/23 ca troceado frozen ket dimar yes yes CO1 G. morhua 100% Salaman lomo de supermar 99.80 131 8/23 ca bacalao frozen ket la plaza yes yes CO1 G. morhua % Salaman filete de supermar 99.84 132 8/23 ca bacalao frozen ket el arbol yes yes CO1 G. morhua % Salaman lomos de supermar pescano 99.84 133 8/23 ca bacalao frozen ket va yes yes CO1 G. morhua % Salaman lomos de supermar

80 134 8/23 ca bacalao frozen ket día yes yes CO1 G. morhua 100% Salaman lomos de supermar 99.84 135 8/23 ca bacalao frozen ket día yes yes CO1 G. morhua % Salaman rodaja de supermar 100% 136 8/23 ca bacalao frozen ket dimar yes yes 16S G. morhua (507/507) Salaman rodaja de supermar 137 8/23 ca bacalao frozen ket dimar yes yes CO1 G. morhua 100% Salaman rodaja de supermar 100% 138 8/23 ca bacalao frozen ket dimar yes yes 16S G. morhua (507/507) Salaman rodaja de supermar 139 8/23 ca bacalao frozen ket dimar yes yes CO1 G. morhua 100% filete Salaman salado al supermar 140 8/23 ca vacio salted ket dimar yes yes CO1 G. morhua 100%

Salaman bacalao supermar 141 8/23 ca troceado salted ket dimar yes yes CO1 G. morhua 100% Salaman bacalao supermar 100% 142 8/23 ca troceado salted ket dimar yes yes 16S G. morhua (492/492) Salaman filete de supermar 99.82 143 8/23 ca bacalao frozen ket dimar yes yes CO1 G. morhua % Salaman filete de supermar 144 8/23 ca bacalao frozen ket dimar yes yes CO1 G. morhua 100% Salaman precook supermar CO1/1 99.3% 145 8/23 ca bolitas ed ket fridela yes yes 6S G. morhua 99% (309/311) recetas Salaman precook supermar artesana 100% 146 8/23 ca croquetas ed ket s no yes 16S G. morhua (407/407) Salaman 81 147 8/24 ca cocochas salted market no yes CO1 G. morhua 100%

Salaman 148 8/24 ca sin espalda salted market no yes CO1 G. morhua 100% Salaman migas de 149 8/24 ca bacalao salted market no yes CO1 G. morhua 100% Salaman migas de 99.84 150 8/24 ca bacalao salted market no yes CO1 G. morhua % Salaman filete de 151 8/24 ca bacalao salted market no yes CO1 G. morhua 100% Salaman migas de 152 8/24 ca bacalao salted market no yes CO1 G. morhua 100% Salaman migas de CO1/1 100% 153 8/24 ca bacalao salted market no yes 6S G. morhua 100% (553/553)

Salaman filete de 154 8/24 ca bacalao salted market no yes CO1 G. morhua 100% Salaman tacos de 155 8/24 ca bacalao salted market no yes CO1 G. morhua 100% Salaman migas de CO1/1 99.36 100% 156 8/24 ca bacalao salted market no yes 6S Molva molva % (524/524) Salaman filete de 157 8/24 ca bacalao frozen market no yes CO1 G. morhua 100% Salaman filete de 100% 158 8/24 ca bacalao frozen market no yes 16S G. morhua (507/507) Salaman filete de 159 8/24 ca bacalao fresh market no no Salaman filete de 100%

82 160 8/24 ca bacalao fresh market no yes 16S G. morhua (507/507)

cola de Salaman bacalao 161 8/24 ca (cod tail) salted market no yes CO1 G. morhua 100% Salaman migas de 162 8/24 ca bacalao salted market no yes CO1 G. morhua 100% Salaman oreja de 99.84 163 8/24 ca bacalao salted market no yes CO1 G. morhua % Salaman palitos CO1/1 99.68 99.6% 164 8/24 ca extra salted market no yes 6S Molva molva % (534/536) Salaman bacalao de supermar froitoma 99.84 165 8/24 ca islandia salted ket r yes yes CO1 G. morhua % Salaman bacalao de supermar froitoma 166 8/24 ca islandia salted ket r yes yes CO1 G. morhua 100%

Salaman bacalao de supermar froitoma 167 8/24 ca islandia salted ket r yes yes CO1 G. morhua 100% Salaman lomo de supermar froitoma 99.83 168 8/24 ca bacalao salted ket r no yes CO1 G. morhua % Salaman bacalao restaura CO1/1 100% 169 8/24 ca ahumado nt restaurant no yes 6S G. morhua 99% (448/448) Salaman bacalao restaura 170 8/24 ca plancha nt restaurant no yes CO1 G. morhua 100% Salaman bacalao con restaura CO1/1 Pollachius 99.84 100% 171 8/25 ca salsa nt restaurant no yes 6S virens % (543/543) Salaman bacalao a la restaura 172 8/25 ca ajohara nt restaurant no yes CO1 G. morhua 100% pimientos del piquillo 83 rellenos de

Salaman bacalao y precook supermar 173 8/26 ca gambas ed ket no no Salaman filete de supermar 174 8/26 ca bacalao frozen ket dia no yes CO1 G. morhua 100% Salaman rodaja de supermar 175 8/26 ca bacalao frozen ket dimar no yes CO1 G. morhua 100% Melanogram Salaman rodaja de supermar mus 99.67 176 8/26 ca bacalao frozen ket dimar no yes CO1 aeglefinus % filete Salaman salado al supermar 177 8/26 ca vacio salted ket dimar yes yes CO1 G. morhua 100% Salaman bacalao supermar 178 8/26 ca desmigado salted ket el arbol no yes CO1 G. morhua 100%

Salaman bacalao a la supermar 179 8/26 ca vizcaina canned ket albo no yes CO1 G. morhua 100% Salaman bacalao a la supermar 180 8/26 ca vizcaina canned ket albo no no Salaman bacalao a la supermar 181 8/26 ca vizcaina canned ket montey no yes CO1 G. morhua 100% Salaman bacalao a la supermar 182 8/26 ca vizcaina canned ket montey no yes CO1 G. morhua 100% Salaman filete de supermar 183 8/26 ca bacalao frozen ket dia no yes CO1 G. morhua 100% Salaman filete de supermar 184 8/26 ca bacalao frozen ket dia no yes CO1 G. morhua 100% Santiag lomo de supermar froitoma 99.4%

84 185 8/27 o bacalao frozen ket r yes yes 16S G. morhua (309/311)

taco Santiag bacalao supermar not 186 8/27 o lonxanova frozen ket labeled yes yes CO1 G. morhua 100% Santiag tacos supermar pescano 99.65 187* 8/27 o bacalao frozen ket va yes yes CO1 G. morhua % Santiag lomo supermar 187* 8/27 o bacalao fresh ket no no Santiag lomo de supermar 188 8/27 o bacalao salted ket gadis no yes CO1 G. morhua 100% Santiag bacalao de supermar froitoma 99.84 189 8/27 o islandia salted ket r yes yes CO1 G. morhua % bacalao de Santiag islandia supermar froitoma 190 8/27 o (ventesa) salted ket r yes yes CO1 G. morhua 100%

bacalao de Santiag islandia supermar froitoma CO1/1 Melanogramm 99.83 99.8% 191 8/27 o (migas) salted ket r yes yes 6S us aeglefinus % (444/445) bacalao de Santiag islandia supermar froitoma CO1/1 Melanogramm 99.83 100% 192 8/27 o (migas) salted ket r yes yes 6S us aeglefinus % (543/543) lomo de Santiag bacalao con restaura 193 8/27 o mango nt restaurant no no Santiag croquetón restaura 194 8/27 o bacalao nt restaurant no no Santiag filete de supermar 195 8/27 o bacalao fresh ket no yes CO1 G. morhua 100% Santiag porciones supermar pescano 196 8/27 o de bacalao frozen ket va no yes CO1 G. morhua 100%

Santiag porciones supermar pescano 99.84 197 8/27 o de bacalao frozen ket va yes yes CO1 G. morhua % Santiag filete de supermar leader 198 8/27 o bacalao frozen ket price no no bacalao posta con Santiag lomo y supermar 100% 199 8/27 o salsa frozen ket yes yes 16S G. morhua (507/507) Santiag filete de supermar 99.84 200 8/27 o bacalao frozen ket no yes CO1 G. morhua % Santiag filete de supermar 99.84 201 8/27 o bacalao frozen ket no yes CO1 G. morhua % Santiag croquetes precook supermar 99.33 202 8/27 o de bacalao ed ket elmar no yes CO1 G. morhua %

Santiag filete de supermar pescano 99.84 203 8/27 o bacalao frozen ket va no yes CO1 G. morhua % Santiag filete de supermar pescano 204 8/27 o bacalao frozen ket va yes yes CO1 G. morhua 100% bacalao Santiag gloria supermar 205 8/27 o lomos salted ket yes yes CO1 G. morhua 100% bacalao Santiag gloria supermar 206 8/27 o lomos salted ket no yes CO1 G. morhua 100% Santiag filete de supermar 207 8/27 o bacalao frozen ket yes yes CO1 G. morhua 100% Santiag bacalao supermar 208 8/27 o congelado frozen ket no yes CO1 G. morhua 100%

86 Santiag bacalao supermar 209 8/27 o congelado frozen ket no yes CO1 G. morhua 100% Santiag filete de supermar 100% 210 8/28 o bacalao frozen ket no yes 16S G. morhua (507/507) Santiag bacalao supermar 99.84 211 8/28 o trozos frozen ket yes yes CO1 G. morhua % Santiag lomo de supermar 100% 212 8/28 o bacalao frozen ket yes yes 16S G. morhua (507/507) Santiag cola de supermar 100% 213 8/28 o bacalao salted ket yes yes 16S G. morhua (507/507) Santiag taco extra supermar 100% 214 8/28 o de bacalao salted ket yes yes 16S G. morhua (507/507) desmigado Santiag extra de supermar 215 8/28 o bacalao salted ket yes yes CO1 G. morhua 100%

Santiag lomo extra supermar 216 8/28 o de bacalao salted ket yes yes CO1 G. morhua 100% Santiag lomito de supermar 100% 217 8/28 o bacalao salted ket yes yes 16S G. morhua (542/542) Santiag lomos de supermar pescano 218 8/28 o bacalao frozen ket va yes yes CO1 G. morhua 100% Santiag lomos de supermar pescano 219 8/28 o bacalao frozen ket va yes yes CO1 G. morhua 100% Santiag centros de supermar 220 8/28 o bacalao salted ket coinba yes yes CO1 G. morhua 100% Santiag centros de supermar 99.84 221 8/28 o bacalao salted ket coinba yes yes CO1 G. morhua % Santiag migas de supermar 99.84

8 222 8/28 o bacalao salted ket coinba yes yes CO1 G. morhua %

bacalao Santiag desalado supermar 99.67 223 8/28 o troceado frozen ket coinba yes yes CO1 G. morhua % bacalao Santiag desalado supermar 224 8/28 o troceado frozen ket coinba yes yes CO1 G. morhua 100% Santiag bacalao a la supermar 225 8/28 o vizcaina canned ket froiz no no Santiag bacalao a la restaura 226 8/28 o gallego nt restaurant no no Santiag restaura 99.83 227 8/28 o bacalao nt restaurant no yes CO1 G. morhua % Santiag cola de 99.84 228 8/29 o bacalao salted market yes yes CO1 G. morhua %

Santiag 229 8/29 o bacalao salted market yes yes CO1 G. morhua 100% Santiag cocochas 230 8/29 o de bacalao salted market yes yes CO1 G. morhua 100% Santiag taco de 231 8/29 o bacalao salted market yes yes CO1 G. morhua 100% Santiag filete de 100% 232 8/29 o bacalao frozen market yes yes 16S G. morhua (507/507) Santiag filete de 100% 233 8/29 o bacalao fresh market yes yes 16S G. morhua (507/507) bacalao Santiag (small Coryphaenoides 99% 234 8/29 o strips) salted market yes yes 16S rupestris (874/874) Santiag bacalao 88 235 8/29 o (flat slice) salted market yes yes CO1 G. morhua 100%

bacalao Santiag (thick 99.84 236 8/29 o square cut) salted market yes yes CO1 G. morhua % Santiag lomo de 237 8/29 o bacalao frozen market yes yes CO1 G. morhua 100% bacalao Santiag (thick 238 8/29 o square cut) frozen market yes yes CO1 G. morhua 100% higado de Santiag bacalao supermar 239 8/29 o (cod liver) canned ket officer no no Santiag huevas de supermar sof 240 8/29 o bacalao canned ket odden no no

tira de Santiag lomo de supermar 241 8/29 o bacalao salted ket royal yes no Santiag filete de supermar 242 8/29 o bacalao fresh ket no no bacalao Santiag salado supermar 243 8/29 o tradicional salted ket dimar yes yes CO1 G. morhua 100% Santiag bacalao supermar carrefou 244 8/29 o filetōn salted ket r no yes CO1 G. morhua 100% Santiag tacos de supermar 245 8/29 o bacalao desalted ket no yes CO1 G. morhua 100% Santiag lomo de supermar 98.37 246 8/29 o bacalao frozen ket yes yes CO1 G. morhua %

89 Santiag huevas de supermar 247 8/29 o bacalao canned ket UBAGO no no Santiag filete de supermar leader 248 8/29 o bacalao frozen ket price yes yes CO1 G. morhua 100% Santiag filete de supermar CO1/1 99.17 100% 249 8/29 o bacalao fresh ket no yes 6S G. morhua % (492/492) Santiag lomo de supermar 250 8/29 o bacalao salted ket outón yes yes CO1 G. morhua 100% Santiag lomo de supermar pescano 251 8/30 o bacalao frozen ket va no yes CO1 G. morhua 100% Santiag sopita de restaura 252 8/30 o bacalao nt restaurant no yes CO1 G. morhua 100% Santiag filete de supermar 253 8/30 o bacalao frozen ket dia no yes CO1 G. morhua 100%

Santiag filete de supermar bacalade 254 8/30 o bacalao frozen ket ra no yes CO1 G. morhua 100% Santiag filete de supermar bacalade 99.84 255 8/30 o bacalao frozen ket ra no yes CO1 G. morhua % bacalao al restaura CO1/1 98.2% 256 9/2 Bilbao pil pil nt restaurant no yes 6S G. morhua 100% (534/544) bacalao a la restaura 257 9/2 Bilbao vizcaina nt restaurant no yes CO1 G. morhua 100% restaura 258 9/2 Bilbao bacalao nt restaurant no yes CO1 G. morhua 100% filete de bacalao supermar CO1/1 Melanogramm 99.67 100% 259 9/2 Bilbao fresco fresh ket yes yes 6S us aeglefinus % (543/543) bacalao supermar 90 260 9/2 Bilbao desalado desalted ket eroski yes yes CO1 G. morhua 100%

bacalao sin supermar 99.84 261 9/2 Bilbao espalda salted ket eroski yes yes CO1 G. morhua % supermar giraldo 262 9/2 Bilbao palitos salted ket esencial yes yes CO1 G. morhua 100% supermar giraldo 263 9/2 Bilbao palitos salted ket esencial yes yes CO1 G. morhua 100% lomos de supermar 264 9/2 Bilbao bacalao frozen ket eroski yes yes CO1 G. morhua 100% lomos de supermar 265 9/2 Bilbao bacalao frozen ket eroski yes yes CO1 G. morhua 100% filete de supermar 99.8% 266 9/2 Bilbao bacalao fresh ket yes yes 16S G. morhua (506/507)

bacalao pimientos supermar 267 9/2 Bilbao piquillo canned ket eroski yes no bacalao pimientos supermar 268 9/2 Bilbao piquillo canned ket eroski no no filete de supermar 100% 269 9/2 Bilbao bacalao frozen ket dia yes yes 16S G. morhua (537/537) porciones supermar pescano 270 9/2 Bilbao de bacalao frozen ket va yes yes CO1 G. morhua 100% filete de supermar tres 100% 271 9/2 Bilbao bacalao frozen ket velas yes yes 16S G. morhua (542/542) filete de supermar tres 100% 272 9/2 Bilbao bacalao frozen ket velas yes yes 16S G. morhua (553/553)

91 bacalao supermar 273 9/2 Bilbao ahumado smoked ket delux yes no bacalao supermar CO1/1 98.29 100% 274 9/2 Bilbao ahumado smoked ket delux no yes 6S G. morhua % (542/542) croquetón restaura CO1/ 99.84 100% 275 9/2 Bilbao de bacalao nt restaurant no yes 16S G. morhua % (542/542) restaura 276 9/2 Bilbao bacalao nt restaurant no no bacalao restaura 100% 277 9/2 Bilbao crujiente nt restaurant no yes 16S G. morhua (542/542) ensalada con lomitos restaura 100% 278 9/2 Bilbao de bacalao nt restaurant no no (542/542) filete de CO1/1 98.97 99.8% 279 9/3 Bilbao bacalao fresh market no yes 6S G. morhua % (541/542)

filete de 100% 280 9/3 Bilbao bacalao fresh market no yes 16S G. morhua (553/553) bacalao 281 9/3 Bilbao alejandra salted market no yes CO1 G. morhua 100% filete de 282 9/3 Bilbao bacalao fresh market no yes CO1 G. morhua 100% filete de 99.84 283 9/3 Bilbao bacalao fresh market no yes CO1 G. morhua % filete de 99.84 284 9/3 Bilbao bacalao fresh market no yes CO1 G. morhua % cocochas 99.84 285 9/3 Bilbao de bacalao fresh market no yes CO1 G. morhua % bacalao

92 286 9/3 Bilbao selecto frozen market no yes CO1 G. morhua 100%

bacalao (small flat 287 9/3 Bilbao cut) frozen market no yes CO1 G. morhua 100% filete de 99.67 288 9/3 Bilbao bacalao fresh market no yes CO1 G. morhua % kokoxa de 289 9/3 Bilbao bacalao fresh market no yes CO1 G. morhua 100% filete de 290 9/3 Bilbao bacalao fresh market no yes CO1 G. morhua 100% filete de 99.8% 291 9/3 Bilbao bacalao fresh market no yes 16S G. morhua (541/542) filete de 292 9/3 Bilbao bacalao fresh market no yes CO1 G. morhua 100%

filete de 98.52 293 9/3 Bilbao bacalao fresh market no yes CO1 G. morhua % bacalao 294 9/3 Bilbao (square cut) salted market no yes CO1 G. morhua 100% croqueta de precook 99.59 295 9/3 Bilbao bacalao ed market no yes CO1 G. morhua % pimiento de precook 99.50 296 9/3 Bilbao bacalao ed market no yes CO1 G. morhua % kokotxas 99.48 297 9/3 Bilbao de bacalao salted market no yes CO1 G. morhua % recortes de 99.50 298 9/3 Bilbao bacalao salted market no yes CO1 G. morhua % bacalao 99.16

93 299 9/3 Bilbao desmigado salted market no yes CO1 G. morhua % colas sin 98.32 300 9/3 Bilbao espinas salted market no yes CO1 G. morhua % colitas de 99.4 301 9/3 Bilbao bacalao salted market no yes CO1 G. morhua % cogotes de 99.8% 302 9/3 Bilbao bacalao salted market no yes 16S G. morhua (552/553) restaura 303 9/4 Bilbao bacalao nt restaurant no no filete de supermar 98.44 304 9/4 Bilbao bacalao frozen ket findus yes yes CO1 G. morhua % bacalao supermar 99.59 305 9/4 Bilbao rebozado frozen ket findus yes yes CO1 G. morhua % bolitas de precook supermar Melanogramm 91% 306 9/4 Bilbao bacalao ed ket friderar yes yes 16S us aeglefinus (616/616)

filete de supermar 307 9/4 Bilbao bacalao fresh ket no yes CO1 G. morhua 100% palitos de bacalao supermar CO1/1 100% 308 9/4 Bilbao rebozados desalted ket alkorta yes yes 6S Molva molva 99.58 (502/502) bacalao supermar super CO1/1 100% 309 9/4 Bilbao desmigado salted ket mar yes yes 6S G. morhua 99.40 (492/492) taco de supermar 310 9/4 Bilbao bacalao salted ket BMC no yes CO1 G. morhua 100% bacalao desalado - supermar 99.59 311 9/4 Bilbao desmigado desalted ket alkorta yes yes CO1 G. morhua % la ventresca supermar baralade 99.84 312 9/4 Bilbao de bacalao frozen ket ra yes yes CO1 G. morhua % 94 la ventresca supermar baralade 99.84 313 9/4 Bilbao de bacalao frozen ket ra yes yes CO1 G. morhua % kokotxas 314 9/5 Bilbao de bacalao fresh market no yes CO1 G. morhua 100% filete de 99.67 315 9/5 Bilbao bacalao fresh market no yes CO1 G. morhua % bacalao supermar 99.83 316 9/5 Bilbao rebozado frozen ket findus yes yes CO1 G. morhua % filete de supermar 317 9/5 Bilbao bacalao frozen ket findus yes yes CO1 G. morhua 100% filete de supermar 318 9/5 Bilbao bacalao frozen ket findus yes no

filete bacalao supermar 99.66 319 9/5 Bilbao salado salted ket no yes CO1 G. morhua % bacalao desmigado supermar 99.84 320 9/5 Bilbao gran salted ket BMC no yes CO1 G. morhua % bacalao desmigado supermar 321 9/5 Bilbao gran salted ket BMC no yes CO1 G. morhua 100% bacalao supermar superma 100% 322 9/5 Bilbao desmigado salted ket r yes yes 16S G. morhua (542/542) bacalao desalado supermar 99.68 99.8% 323 9/5 Bilbao palitos desalted ket yes yes CO1 Molva molva % (546/547) bacalao desalado supermar 99.68 100%

324 9/5 Bilbao palitos desalted ket yes yes CO1 Molva molva % (536/536) filete de supermar 325 9/5 Bilbao bacalao frozen ket dimar yes yes CO1 G. morhua 100% filete de supermar 326 9/5 Bilbao bacalao frozen ket dimar yes yes CO1 G. morhua 100% bacalao islandia supermar not 99.83 327 9/5 Bilbao unidad salted ket labeled yes yes CO1 G. morhua % Barcelo bacalao CO1/1 99.84 99.4% 328 9/6 na (square cut) salted market no yes 6S Molva molva % (492/495) Barcelo recortes de 100% 329 9/6 na bacalao salted market no yes 16S G. morhua (542/542) Barcelo higado de 330 9/6 na bacalao canned market no no

Barcelo lomos de supermar 331 9/6 na bacalao frozen ket no yes CO1 G. morhua 100% Barcelo lomos de supermar 332 9/6 na bacalao frozen ket yes yes CO1 G. morhua 100% Barcelo filete de supermar 333 9/6 na bacalao frozen ket findus yes yes CO1 G. morhua 100% huevos de Barcelo bacalao supermar 334 9/6 na (cod eggs) canned ket DANI no no Barcelo filete de supermar 335 9/6 na bacalao frozen ket condis no yes CO1 G. morhua 100% Barcelo filete de supermar 336 9/6 na bacalao frozen ket condis yes yes CO1 G. morhua 100% Barcelo lomos de supermar 99.84 96 337 9/6 na bacalao frozen ket findus yes yes CO1 G. morhua %

tira de Barcelo lomo de supermar 99.84 338 9/6 na bacalao salted ket royal yes yes CO1 G. morhua % Barcelo carpaccio supermar 99.65 339 9/6 na de bacalao salted ket gomá no yes CO1 G. morhua % Barcelo brandada supermar benfuma 340 9/6 na de bacalao fresh ket t no no Barcelo recortes de 99.84 341 9/6 na bacalao salted market no yes CO1 G. morhua % Barcelo bacalao CO1/1 99.68 100% 342 9/6 na (square cut) salted market no yes 6S Molva molva % (531/531) Barcelo filete de 100% 343 9/6 na bacalao salted market no yes 16S G. morhua (507/507)

Barcelo lomo de 99.66 344 9/6 na bacalao salted market no yes CO1 G. morhua % Barcelo cola de 99.84 345 9/6 na bacalao salted market no yes CO1 G. morhua % Barcelo palito de 98.21 346 9/6 na bacalao salted market no yes CO1 G. morhua % Barcelo esquixada 99.68 347 9/6 na de bacalao salted market no yes CO1 G. morhua % Barcelo filete supermar carrefou 348 9/7 na bacalao fresh ket r yes no Barcelo desmigado supermar CO1/1 99.6% 349 9/7 na bacalao salted ket dimar yes yes 6S Molva molva 100% (533/535) Barcelo desmigado supermar 99.84

97 350 9/7 na bacalao salted ket dimar yes yes CO1 G. morhua %

bacalao Barcelo surtido supermar carrefou 351 9/7 na ahumado smoked ket r yes no Barcelo tacos de supermar 100% 352 9/7 na bacalao fresh ket yse yes 16S G. morhua (507/507) Barcelo crema de precook supermar 100% 353 9/7 na bacalao ed ket royal yes yes 16S G. morhua (409/409) bacalao con Barcelo cebello y restaura 354 9/7 na pimientos nt restaurant no yes CO1 G. morhua 100% Barcelo croquetas restaura CO1/1 Pollachius 98.01 100% 355 9/7 na de bacalao nt restaurant no yes 6S virens % (507/507) Barcelo bacalao restaura 356 9/8 na doughnut nt restaurant no yes CO1 G. morhua 100%

Barcelo bacalao restaura 100% 357 9/8 na fritters nt restaurant no yes 16S G. morhua (507/507) Barcelo restaura 100% 358 9/9 na bacalao nt restaurant no yes 16S G. morhua (507/507) Barcelo bacalao 100% 359 9/9 na sunfaina frozen market gala no yes 16S G. morhua (407/407) Barcelo bacalao 360 9/9 na llauna frozen market no no Barcelo bacalao precook CO1/1 Pollachius 99.84 100% 361 9/9 na tratufas ed market no yes 6S virens % (543/543) Barcelo croquetas precook 362 9/9 na de bacalao ed market no yes CO1 G. morhua 100% Barcelo bacalao

98 363 9/9 na "lloms" frozen market no yes CO1 G. morhua 100% Barcelo bacalao 99.84 364 9/9 na pencas frozen market no yes CO1 G. morhua % Barcelo lomo CO1/1 100% 365 9/9 na bacalao desalted market no yes 6S G. morhua 100% (553/553) Barcelo bacalao de 99.69 366 9/9 na islandia salted market no yes CO1 G. morhua % bacalao Barcelo pencas 99.82 367 9/9 na islandia salted market no yes CO1 G. morhua % lomito de Barcelo bacalao sin 368 9/9 na espina salted market no yes CO1 G. morhua 100% tacos de Barcelo bacalao sin 369 9/9 na espina salted market no yes CO1 G. morhua 100%

Barcelo tacos de 370 9/9 na bacalao salted market no yes CO1 G. morhua 100% Barcelo esqueitxada 99.83 371 9/9 na de bacalao frozen market no yes CO1 G. morhua % Barcelo croquetas precook 372 9/9 na de bacalao ed market no yes CO1 G. morhua 100% Barcelo cola de 373 9/9 na bacalao salted market no yes CO1 G. morhua 100% Barcelo taco de 99.84 374 9/9 na bacalao salted market no yes CO1 G. morhua % Barcelo lomo de 375 9/9 na bacalao salted market no yes CO1 G. morhua 100% Barcelo esqueitxada

99 376 9/9 na de bacalao salted market no yes CO1 G. morhua 100%

bacalao con Barcelo cebello y 100% 377 9/9 na pimientos fresh market no yes 16S G. morhua (448/448) Barcelo bacalao restaura 99.84 378 9/9 na ensalada nt restaurant no yes CO1 G. morhua % Barcelo morro de supermar 99.8% 379 9/9 na bacalao frozen ket la sirena yes yes 16s G. morhua (536/537) Barcelo lomo de supermar 380 9/9 na bacalao frozen ket la sirena yes yes CO1 G. morhua 100% bacalao Barcelo esqueixada supermar 99.2% 381 9/9 na desalada desalted ket la sirena no yes 16S G. morhua (510/514) lomo Barcelo selecto de supermar 382 9/9 na bacalao frozen ket la sirena yes yes CO1 G. morhua 100%

Barcelo tacos de supermar 383 9/9 na bacalao frozen ket la sirena yes yes CO1 G. morhua 100% Barcelo bacalao de supermar 384 9/9 na islandia frozen ket la sirena yes yes CO1 G. morhua 100% Barcelo piquillo de supermar 385 9/9 na bacalao frozen ket la sirena yes yes CO1 G. morhua 100% Barcelo lomo de 386 9/10 na bacalao salted market no yes CO1 G. morhua 100% bacalao Barcelo (small flat 387 9/10 na cut) salted market no yes CO1 G. morhua 100% Barcelo bacalao 99.83 388 9/10 na (flat cut) salted market no yes CO1 G. morhua %

100 Barcelo bacalao 389 9/10 na labrador salted market no yes CO1 G. morhua 100% filete de Barcelo bacalao 99.84 390 9/10 na ingles salted market no yes CO1 G. morhua % Barcelo filete de 391 9/10 na bacalao fresh market no yes CO1 G. morhua 100% Barcelo filete de 99.84 392 9/10 na bacalao fresh market no yes CO1 G. morhua % Barcelo cola de 99.84 393 9/10 na bacalao salted market no yes CO1 G. morhua % Barcelo filete de 394 9/10 na bacalao desalted market no no bacalao Barcelo (very small 100% 395 9/10 na end cut) desalted market no yes 16S G. morhua (542/542)

Barcelo migas de 99.83 396 9/10 na bacalao salted market no yes CO1 G. morhua % Barcelo filetón de supermar 99.63 397 9/10 na bacalao salted ket yes yes CO1 G. morhua % Barcelo filete de supermar 100% 398 9/10 na bacalao fresh ket no yes 16S G. morhua (542/542) Barcelo migas de supermar 399 9/10 na bacalao salted ket angomar yes yes CO1 G. morhua 100% Barcelo supremas supermar 400 9/10 na de bacalao frozen ket eskimo yes yes CO1 G. morhua 100% Barcelo migas de supermar 99.84 401 9/10 na bacalao salted ket comsum yes yes CO1 G. morhua % Barcelo mousse de precook supermar 100%

101 402 9/10 na bacalao ed ket angomar yes yes 16S G. morhua (542/542)

Barcelo bacalao supermar 403 9/10 na ahumado smoked ket royal yes yes CO1 G. morhua 100% Barcelo filete de supermar 404 9/10 na bacalao fresh ket no yes CO1 G. morhua 100% Barcelo filete de supermar pescano CO1/1 100% 405 9/10 na bacalao frozen ket va yes yes 6S G. morhua 100% (553/553) Barcelo bacalao restaura 99.23 406 9/10 na llauna nt restaurant no yes CO1 G. morhua % Barcelo bacalao restaura 407 9/10 na llauna nt restaurant no yes CO1 G. morhua 100% Barcelo supermar 100% 408 9/10 na bacalao fresh ket caladero yes yes 16S G. morhua (542/542) Barcelo filete de supermar maredeu 409 9/10 na bacalao frozen ket s yes yes CO1 G. morhua 100%

Barcelo tacos de supermar maredeu 410 9/10 na bacalao frozen ket s yes yes CO1 G. morhua 100% Gadus Barcelo migas de supermar macrocephalu 99.84 100% 411 9/10 na bacalao salted ket UBAGO yes yes CO1 s % (992/992) lomo Barcelo suprema de supermar maredeu 412 9/10 na bacalao frozen ket s yes yes CO1 G. morhua 100% Barcelo migas de supermar 413 9/10 na bacalao salted ket UBAGO yes yes CO1 G. morhua 100% Barcelo huevos de supermar 414 9/10 na bacalao canned ket DANI no no Barcelo higado de supermar 415 9/10 na bacalao canned ket UBAGO no no

102 Barcelo bacalao a la supermar hacenda

416 9/10 na vizcaina canned ket do no no Barcelo bacalao restaura 100% 417 9/11 na ahumado nt restaurant no yes 16S G. morhua (542/542) Barcelo bacalao a restaura 418 9/11 na samfaina nt restaurant no yes CO1 G. morhua 100% Barcelo pimientos restaura 99.84 419 9/11 na con bacalao nt restaurant no yes CO1 G. morhua % Valenci fish (cod) restaura 99.84 420 9/12 a and chips nt restaurant no yes CO1 G. morhua % bacalao Valenci (small flat 421 9/13 a cut) salted market no yes CO1 G. morhua 100% Valenci migas de 422 9/13 a bacalao desalted market no yes CO1 G. morhua 100%

Valenci bacalao 423 9/13 a ahumado smoked market no no Valenci bacalao 424 9/13 a labrador salted market no yes CO1 G. morhua 100% Gadus 100% Valenci migas de CO1/1 chalcogrammu 99.83 (1013/10 425 9/13 a bacalao salted market no yes 6S s % 13) Valenci filete de 99.6% 426 9/13 a bacalao fresh market no yes 16S G. morhua (540/542) Valenci bacalao al 427 9/13 a pil-pil fresh market no yes CO1 G. morhua 100% Valenci bacalao al 428 9/13 a pil-pil salted market no yes CO1 G. morhua 100%

103 Valenci migas de 429 9/13 a bacalao salted market no yes CO1 G. morhua 100%

Valenci filete de 430 9/13 a bacalao fresh market no yes CO1 G. morhua 100% Valenci filete de 99.83 431 9/13 a bacalao fresh market no yes CO1 G. morhua % Valenci filete de 432 9/13 a bacalao fresh market no no Valenci whole CO1/1 Merluccius 99.5% 433 9/13 a small cod fresh market no yes 6S merluccius 100% (555/558) Valenci bacalao 99.67 434 9/13 a ahumado smoked market no yes CO1 G. morhua % Valenci cocochas 435 9/13 a de bacalao fresh market no yes CO1 G. morhua 100%

Valenci lomo de 436 9/13 a bacalao salted market no yes CO1 G. morhua 99.83 Valenci pasta de precook 99.83 437 9/13 a bacalao ed market no yes CO1 G. morhua % Valenci lomo de 438 9/13 a bacalao desalted market no yes CO1 G. morhua 100% Valenci bacalao 99.63 439 9/13 a labrador salted market no yes CO1 G. morhua % Valenci lomo de 440 9/13 a bacalao salted market no yes CO1 G. morhua 100% Valenci bacalao 441 9/13 a labrador salted market no yes CO1 G. morhua 100% Valenci pasta de precook

104 442 9/13 a bacalao ed market no yes CO1 G. morhua 100%

Valenci filete de 443 9/13 a bacalao salted market no yes CO1 G. morhua 100% Valenci cola de 444 9/13 a bacalao salted market no yes CO1 G. morhua 100% Valenci croquetas restaura 445 9/13 a de bacalao nt restaurant no no Gadus Valenci croquetas CO1/1 chalcogrammu 100% 446 9/14 a de bacalao frozen market no yes 6S s 100% (548/548) Valenci bacalao 447 9/14 a ahumado smoked market no yes CO1 G. morhua 100% Valenci bacalao supermar 99.84 448 9/14 a labrador salted ket UBAGO yes yes CO1 G. morhua %

bacalao con Valenci pimientos y restaura 99.84 449 9/14 a atún nt restaurant no yes CO1 G. morhua % Valenci bacalao supermar cozha 450 9/14 a dorado frozen ket pronto no no Valenci tacos de supermar CO1/1 99.34 100% 451 9/14 a bacalao frozen ket mardeus yes yes 6S G. morhua % (553/553) Valenci filete de supermar 452 9/14 a bacalao frozen ket mardeus yes yes CO1 G. morhua 100% Valenci bacalao a la supermar hacenda 453 9/14 a vizcaina canned ket do no no Valenci bacalao supermar eurosan 454 9/14 a ahumado smoked ket h yes yes CO1 G. morhua 100% aspecto de 105 los centros

Valenci de bacalao supermar la 455 9/14 a desalada desalted ket balinesa yes yes CO1 G. morhua 100% Valenci filete de supermar mare 99.68 456 9/14 a bacalao fresh ket nostrum yes yes CO1 G. morhua % Valenci desmigado supermar 99.84 457 9/14 a de bacalao salted ket yes yes CO1 G. morhua % Valenci bacalao supermar 99.84 458 9/14 a troceado salted ket yes yes CO1 G. morhua % Valenci bacalao supermar 459 9/14 a desmigado salted ket no yes CO1 G. morhua 100% Valenci bacalao supermar 99.84 460 9/14 a salado salted ket Gaytón yse yes CO1 G. morhua % Valenci bacalao supermar ahumad 99.84 461 9/14 a ahumado smoked ket os yes yes CO1 G. morhua %

domingu ez

Valenci filete de supermar 462 9/14 a bacalao frozen ket aliada yes yes CO1 G. morhua 100% bacalao de Valenci islandia supermar la 463 9/14 a ahumado smoked ket higuerta yes yes CO1 G. morhua 100% Valenci bacalao supermar 464 9/14 a rebozado frozen ket findus yes yes CO1 G. morhua 100% Valenci bacalao a la supermar cabo de 465 9/14 a vizcaina fresh ket peñas no no Valenci bacalao al supermar 100% 466 9/14 a pil-pil canned ket no yes 16S G. morhua (542/542)

106 Valenci higado de supermar 100% 467 9/14 a bacalao canned ket UBAGO no yes 16S G. morhua (316/316)

Valenci huevos de supermar 468 9/14 a bacalao canned ket Usista no no Valenci bacalao a la restaura CO1/1 Pollachius 99.84 100% 469 9/15 a llauna nt restaurant no yes 6S virens % (543/543) Valenci bacalao con precook supermar salares- 470 9/15 a pimientos ed ket car yes yes CO1 G. morhua 100% Valenci bacalao supermar carrefou 471 9/15 a salado salted ket r yes yes CO1 G. morhua 100% Valenci bacalao supermar 99.84 472 9/15 a lomo extra frozen ket yes yes CO1 G. morhua % Valenci bacalao supermar 99.84 473 9/15 a lomo extra frozen ket no yes CO1 G. morhua %

lomo Valenci selecto de supermar 474 9/15 a bacalao salted ket royal yes yes CO1 G. morhua 100% Valenci bacalao supermar carrefou 100% 475 9/15 a ahumado smoked ket r no yes 16S G. morhua (542/542) Valenci lomos de supermar 476 9/16 a bacalao frozen ket día no yes CO1 G. morhua 100% Valenci lomos de supermar 477 9/16 a bacalao frozen ket día yes yes CO1 G. morhua 100% Valenci filete de supermar pescano 478 9/16 a bacalao frozen ket va yes yes CO1 G. morhua 100% Valenci huevos de supermar 99.8% 479 9/16 a bacalao canned ket SOF no yes 16S G. morhua (542/543)

107 Valenci higado de supermar 480 9/16 a bacalao canned ket officer no no tiro de Valenci lomos de supermar 98.89 481 9/16 a bacalao desalted ket royal yes yes CO1 G. morhua % 100% Valenci filete de supermar (542/254 482 9/16 a bacalao fresh ket no yes 16S G. morhua 2) Valenci tacos de supermar 483 9/16 a bacalao frozen ket exkimo yes yes CO1 G. morhua 100% Valenci filete de supermar 98.91 484 9/16 a bacalao fresh ket no yes CO1 G. morhua % Valenci bacalao supermar 99.84 485 9/16 a labrador salted ket UBAGO yes yes CO1 G. morhua % Valenci lomo de supermar 99.67 486 9/16 a bacalao frozen ket mardeus no yes CO1 G. morhua %

Valenci bacalao al supermar 99.8% 487 9/16 a pil-pil fresh ket no yes 16S G. morhua (541/542) Valenci filete de supermar 99.84 488 9/16 a bacalao frozen ket mardeus no yes CO1 G. morhua % Valenci filete de supermar 99.8% 489 9/16 a bacalao frozen ket mardeus no yes 16S G. morhua (541/542) Valenci croquetas restaura 490 9/16 a de bacalao nt restaurant no yes CO1 G. morhua 100% Valenci tacos de restaura 491 9/16 a bacalao nt restaurant no yes CO1 G. morhua 100% taquitas de restaura 492 10/18 Seville bacalao nt restaurant no yes CO1 G. morhua 100% filete de supermar

108 493 10/18 Seville bacalao frozen ket día no yes CO1 G. morhua 100%

huevos de supermar 494 10/18 Seville bacalao canned ket UBAGO no no filete de supermar 99.83 495 10/18 Seville bacalao fresh ket no yes CO1 G. morhua % filete de supermar tres 99.84 496 10/18 Seville bacalao frozen ket velas yes yes CO1 G. morhua % filete de supermar tres 497 10/18 Seville bacalao frozen ket velas yes yes CO1 G. morhua 100% filete de supermar 100% 498 10/18 Seville bacalao frozen ket admiral yes yes 16S G. morhua (542/542) bacalao supermar 499 10/18 Seville ahumado smoked ket yes no bacalaos y supermar 500 10/18 Seville pimientos fresh ket UBAGO no no

bacalao supermar 501 10/18 Seville ahumado smoked ket UBAGO no no bacalao supermar 99.83 502 10/18 Seville labrador salted ket UBAGO yes yes CO1 G. morhua % tacos de supermar 503 10/18 Seville bacalao frozen ket mardeus no yes CO1 G. morhua 100% filete de supermar 99.84 504 10/18 Seville bacalao fresh ket caladero no yes CO1 G. morhua % albóndigas precook supermar 99.84 505 10/18 Seville de bacalao ed ket camós no yes CO1 G. morhua % bacalao al supermar 99.8% 506 10/18 Seville pil-pil fresh ket caladero on yes 16S G. morhua (542/543) desmigado

109 tiro de lomo de supermar 507 10/18 Seville bacalao salted ket royal yes yes CO1 G. morhua 100% higado de supermar 508 10/18 Seville bacalao canned ket officer no no huevos de supermar 509 10/18 Seville bacalao canned ket SOF no no bacalao supermar 100% 510 10/18 Seville ahumado smoked ket MAS no yes 16S G. morhua (542/542) lomos selectos de supermar CO1/1 99.84 100% 511 10/18 Seville bacalao salted ket MAS no yes 6S G. morhua % (542/542) lomos selectos de supermar 99.67 512 10/18 Seville bacalao salted ket MAS no yes CO1 G. morhua %

bacalao precook supermar terranov 99.52 513 10/18 Seville dorado ed ket a yes yes CO1 G. morhua % filete de supermar 98.36 514 10/18 Seville bacalao fresh ket no yes CO1 G. morhua % bacalao supermar CO1/1 99.52 100% 515 10/18 Seville desmigado salted ket barear no yes 6S Molva molva % (541/541) bacalao supermar 99.52 100% 516 10/18 Seville desmigado salted ket barear no yes CO1 Molva molva % (985/985) filete de 517 10/19 Seville bacalao fresh market no no filete de 98.69 518 10/19 Seville bacalao fresh market no yes CO1 G. morhua % filete de

110 519 10/19 Seville bacalao fresh market no no

bacalao al 520 10/19 Seville pil-pil fresh market no yes CO1 G. morhua 1.00 bacalao con restaura 99.18 521 10/19 Seville ratatouie nt restaurant no yes CO1 G. morhua % lomo supreme de 99.63 522 10/19 Seville bacalao salted market no yes CO1 G. morhua % tira de filetón de 523 10/19 Seville bacalao salted market no yes CO1 G. morhua 100% filete de 524 10/19 Seville bacalao fresh market no yes CO1 G. morhua 100% filete de 100% 525 10/19 Seville bacalao fresh market no yes 16S G. morhua (542/542)

filete de 98.94 89% 526 10/19 Seville bacalao fresh market no yes CO1 Sparus aurata % (760/760) cocochas 99.84 527 10/19 Seville de bacalao salted market no yes CO1 G. morhua % desmigado 99.49 528 10/19 Seville de bacalao salted market no yes CO1 G. morhua % bacalao 100% 529 10/19 Seville ahumado smoked market martico yes yes 16S G. morhua (537/537) Pangasianodo n palito de CO1/1 hypophthalmu 98.52 546/548 530 10/19 Seville bacalao frozen market no yes 6S s % (99.6%) croquetas precook 99.8% 531 10/19 Seville de bacalao ed market no yes 16S G. morhua (513/514) 111 lomito de 99.84

532 10/19 Seville bacalao frozen market no yes CO1 G. morhua % bacalao supermar 99.84 533 10/19 Seville desmigado salted ket dimar no yes CO1 G. morhua % bacalao supermar 99.67 534 10/19 Seville desmigado salted ket dimar no yes CO1 G. morhua % Gadus bacalao supermar chalcogrammu 99.8% 535 10/19 Seville desmigado salted ket supersol no yes 16S s (543/544) bacalao supermar selectos 100% 536 10/19 Seville ahumado smoked ket de mar yes yes 16S G. morhua (548/548) lomo de supermar pescano 99.84 537 10/19 Seville bacalao frozen ket va yes yes CO1 G. morhua % tacos de supermar 99.84 538 10/19 Seville bacalao frozen ket barear yes yes CO1 G. morhua %

tacos de supermar 539 10/19 Seville bacalao frozen ket barear yes yes CO1 G. morhua 100% filete de supermar 99.68 540 10/19 Seville bacalao fresh ket no yes CO1 G. morhua % lomo supremo de supermar not 541 10/19 Seville bacalao frozen ket labeled yes yes CO1 G. morhua 100% bacalao supermar carrefou 99.84 542 10/19 Seville salado salted ket r yes yes CO1 G. morhua % bacalao supermar carrefou CO1/1 Melanogramm 99.65 100% 543 10/19 Seville salado salted ket r yes yes 6S us aeglefinus % (543/543) bacalao supermar el corte 544 10/19 Seville ahumado smoked ket ingles yes yes CO1 G. morhua 100%

112 bacalao supermar 98.85 545 10/19 Seville troceado salted ket royal yes yes CO1 G. morhua %

filete de supermar 99.84 546 10/19 Seville bacalao frozen ket findus yes yes CO1 G. morhua % solomilla de rodajas supermar 99.83 547 10/19 Seville de bacalao frozen ket royal yes yes CO1 G. morhua % solomilla de rodajas supermar 99.83 548 10/19 Seville de bacalao frozen ket royal yes yes CO1 G. morhua % bacalao supermar 99.50 549 10/19 Seville desalado desalted ket gaytán yes yes CO1 G. morhua % bacalao supermar 99.84 550 10/19 Seville desalado desalted ket gaytán yes yes CO1 G. morhua % bacalao precook supermar 99.34 551 10/19 Seville frito ed ket no yes CO1 G. morhua %

palito de supermar 99.50 552 10/19 Seville bacalao salted ket no yes CO1 G. morhua % huevos de supermar 100% 553 10/19 Seville bacalao canned ket diamar no yes 16S G. morhua (542/542) bacalao a la supermar 99.4% 554 10/19 Seville vizcaina canned ket diamar no yes 16S G. morhua (541/544) huevos de supermar 99.6% 555 10/19 Seville bacalao canned ket usisa no yes 16S G. morhua (512/514) bacalao restaura 556 10/19 Seville gatinada nt restaurant fripozo no yes CO1 G. morhua 100 buñuelos precook supermar CO1/1 Pollachius 99.83 100% 557 10/19 Seville de bacalao ed ket no yes 6S virens % (543/543) bacalao restaura

113 558 10/19 Seville frito nt restaurant no yes CO1 G. morhua 100

ensalada de acacado y restaura 100% 559 10/20 Seville bacalao nt restaurant no yes 16S G. morhua (553/553) berenjena y restaura CO1/1 99.65 100% 560 10/20 Seville bacalao nt restaurant no yes 6S G. morhua % (537/537) pan y restaura 99.84 561 10/20 Seville bacalao nt restaurant no yes CO1 G. morhua % bacalao restaura 99.63 562 10/20 Seville frito nt restaurant no yes CO1 G. morhua % bacalao supermar 99.67 563 10/24 Granada desmigado salted ket dimar yes yes CO1 G. morhua % filete de supermar 99.35 564 10/24 Granada bacalao frozen ket dimar yes yes CO1 G. morhua %

troceado de supermar 99.68 565 10/24 Granada bacalao frozen ket dimar yes yes CO1 G. morhua % bacalao de supermar selectos 99.84 566 10/24 Granada islandia smoked ket de mar yes yes CO1 G. morhua % bacalao supermar 99.51 567 10/24 Granada desmigado salted ket eroski yes yes CO1 G. morhua % lomo de supermar 568 10/24 Granada bacalao frozen ket eroski yes yes CO1 G. morhua 100% lomo de supermar 99.84 569 10/24 Granada bacalao frozen ket yes yes CO1 G. morhua % lomo de supermar 99.8% 570 10/24 Granada bacalao frozen ket yes yes 16S G. morhua (543/544) lomos de supermar

114 571 10/24 Granada bacalao frozen ket coviran yes yes CO1 G. morhua 100%

bacalao precook supermar 572 10/24 Granada rebozado ed ket coviran yes no filete de supermar 99.82 573 10/24 Granada bacalao frozen ket día yes yes CO1 G. morhua % lomo de supermar pescano 100% 574 10/24 Granada bacalao frozen ket va yes yes 16S G. morhua (553/553) filete de supermar pescano 575 10/24 Granada bacalao frozen ket va yes yes CO1 G. morhua 100% bacalao supermar 99.35 576 10/24 Granada plancha fresh ket no yes CO1 G. morhua % croquetas supermar CO1/1 98.37 100% 577 10/24 Granada de bacalao fresh ket no yes 6S G. morhua % (542/542) filete de supermar 100% 578 10/24 Granada bacalao fresh ket no yes 16S G. morhua (553/553)

filete de supermar 100% 579 10/24 Granada bacalao fresh ket no yes 16S G. morhua (537/537) bacalao supermar 99.84 580 10/24 Granada ahumado smoked ket hipercor yes yes CO1 G. morhua % bacalao de supermar selectos 99.34 581 10/24 Granada islandia smoked ket de mar yes yes CO1 G. morhua % bacalao precook supermar 582 10/24 Granada rebozado ed ket fidus yes yes CO1 G. morhua 100% bacalao ultracongel supermar 99.01 583 10/24 Granada ado frozen ket royal yes yes CO1 G. morhua % bacalao supermar 99.84 584 10/24 Granada gaytán salted ket gaytán yes yes CO1 G. morhua %

115 bacalao supermar 585 10/24 Granada gaytán salted ket gaytán yes yes CO1 G. morhua 100%

croquetas precook supermar 586 10/24 Granada de bacalao ed ket alidada no no croquetas precook supermar la 99.8% 587 10/24 Granada de bacalao ed ket cocinera no yes 16S G. morhua (513/514) palitos de supermar 99.84 588 10/24 Granada bacalao salted ket royal no yes CO1 G. morhua % palitos de supermar 99.84 589 10/24 Granada bacalao salted ket royal no yes CO1 G. morhua % huevos de supermar 99.4% 590 10/24 Granada bacalao canned ket officer no yes 16S G. morhua (511/514) huevos de supermar 591 10/24 Granada bacalao canned ket tejero no no

lomo de 100% 592 10/25 Granada bacalao salted market no yes 16S G. morhua (553/553) bacalao 100% 593 10/25 Granada labrador salted market no yes 16S G. morhua (553/553) Pangasianodo n bacalao restaura hypophthalmu 100% 594 10/26 Granada revuelto nt restaurant no yes 16S s (872/872) tacos de 595 10/26 Granada bacalao frozen market no yes CO1 G. morhua 100% migas de 596 10/26 Granada bacalao frozen market no yes CO1 G. morhua 100% cola de 99.47 597 10/26 Granada bacalao frozen market no yes CO1 G. morhua % 116 bacalao 99.6%

598 10/26 Granada selecto frozen market yes yes 16S G. morhua (512/514) pimientos de piquillo rellenos de precook 99.35 599 10/26 Granada bacalao ed market no yes CO1 G. morhua % bacalao a la precook 98.82 600 10/26 Granada vizcaina ed market no yes CO1 G. morhua % bacalao al restaura 601 10/26 Granada pil-pil nt restaurant no no croquetas restaura 602 10/26 Granada de bacalao nt restaurant no no bacalao (thin-cut 99.84 603 10/26 Granada stripes) fresh market no yes CO1 G. morhua %

cocochas 99.51 604 10/26 Granada de bacalao fresh market no yes CO1 G. morhua % migas de 99.84 605 10/26 Granada bacalao salted market no yes CO1 G. morhua % migas de 98.50 606 10/26 Granada bacalao salted market no yes CO1 G. morhua % pimientos de piquillo 607 10/26 Granada de bacalao canned market celorrio no no filete de supermar CO1/1 100% 608 10/31 Granada bacalao fresh ket no yes 6S G. morhua 99.84 (553/553) bacalao al precook supermar 100% 609 10/31 Granada pil-pil ed ket no yes 16S G. morhua (542/542)

117 huevos de supermar 610 10/31 Granada bacalao canned ket officer no no brisa tortillas de precook supermar dorada 611 10/31 Granada bacalao ed ket mariscas no no bacalao supermar 612 10/31 Granada desalado desalted ket royal no no bacalao supermar 99.67 613 10/31 Granada desalado desalted ket royal yes yes CO1 G. morhua % bacalao supermar super 99.82 614 10/31 Granada ventresca salted ket mar yes yes CO1 G. morhua % bacalao supermar super 99.70 615 10/31 Granada ventresca salted ket mar yes yes CO1 G. morhua % bacalao rebozado supermar 99.84 616 10/31 Granada (filete) frozen ket findus yes yes CO1 G. morhua %

croquetas precook supermar el corte CO1/1 Pollachius 99.84 99.8% 617 10/31 Granada de bacalao ed ket ingles no yes 6S virens % (543/544) bacalao ultracongel supermar 99.67 618 10/31 Granada ado frozen ket royal yes yes CO1 G. morhua % filete de supermar 99.18 619 10/31 Granada bacalao frozen ket aliada yes yes CO1 G. morhua % ahumad os bacalao supermar domingu 100% 620 10/31 Granada ahumado smoked ket ez yes yes 16S G. morhua (542/542) filete de 99.84 621 11/1 Granada bacalao frozen market no yes CO1 G. morhua % filete de 99.84

118 622 11/1 Granada bacalao fresh market no yes CO1 G. morhua %

filete de 99.84 623 11/1 Granada bacalao fresh market no yes CO1 G. morhua % filete de 624 11/1 Granada bacalao fresh market no no filete de 625 11/1 Granada bacalao fresh market no no filete de 626 11/1 Granada bacalao fresh market no no filete de 99.84 627 11/1 Granada bacalao fresh market no yes CO1 G. morhua % filete de 628 11/1 Granada bacalao fresh market no no bacalao con restaura CO1/1 Micromesistiu 99.2% 629 11/2 Granada pan nt restaurant no yes 6S s poutassou 100% (544/548)

esquilado restaura 99.84 630 11/2 Granada de bacalao nt restaurant no yes CO1 G. morhua % croquestas restaura 631 11/2 Granada de bacalao nt restaurant no no bacalao restaura 632 11/2 Granada frito nt restaurant no no bacalao con restaura 633 11/2 Granada tomate nt restaurant no no Table A.1: Complete sample data. Adjascent samples with identical blue backgrounds indicate that the samples came from the same package. Two samples with * were mistakenly recorded with the same sample number.

119