Journal of Marine Systems 75 (2009) 305–313

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Journal of Marine Systems

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Heavy metals in edible seaweeds commercialised for human consumption

Victoria Besada a,⁎, José Manuel Andrade b,1, Fernando Schultze a,2, Juan José González a,2

a Centro Oceanográfico de Vigo, Instituto Español de Oceanografía, Apdo. 1552, 36200 Vigo, Spainb Departamento de Química Analítica, Universidad de A Coruña, Campus da Zapateira s/n 15071, A Coruña, Spain

a r t i c l e i n f o

⁎ Corresponding author. Tel.: +34 986492111; fax: +E-mail addresses: victoria.besada@vi.ieo.es (V. Besa

(J.M. Andrade), fernando.schultze@vi.ieo.es (F. Schultzjjose.gonzalez@vi.ieo.es (J.J. González).

1 Tel.: +34 981167000; fax: +34 981167065.2 Tel.: +34 986492111; fax: +34 986498626.

0924-7963/$ – see front matter © 2008 Elsevier B.V.doi:10.1016/j.jmarsys.2008.10.010

a b s t r a c t

Article history:Received 28 September 2007Received in revised form 14 October 2008Accepted 21 October 2008Available online 29 October 2008

Though seaweed consumption is growing steadily across Europe, relatively few studies havereported on the quantities of heavy metals they contain and/or their potential effects on thepopulation's health. This study focuses on the first topic and analyses the concentrations of sixtypical heavy metals (Cd, Pb, Hg, Cu, Zn, total As and inorganic As) in 52 samples from 11 algae-based products commercialised in Spain for direct human consumption (Gelidium spp.; Eiseniabicyclis; Himanthalia elongata; Hizikia fusiforme; Laminaria spp.; Ulva rigida; Chondrus crispus;Porphyra umbilicales and Undaria pinnatifida).Samples were ground, homogenised and quantified by atomic absorption spectrometry (Cu andZn by flame AAS; Cd, Pb and total As by electrothermal AAS; total mercury by the cold vapourtechnique; and inorganic As by flame-hydride generation). Accuracy was assessed byparticipation in periodic QUASIMEME (Quality Assurance of Information in MarineEnvironmental Monitoring in Europe) and IAEA (International Atomic Energy Agency)intercalibration exercises. To detect any objective differences existing between the seaweeds'metal concentrations, univariate and multivariate studies (principal component analysis,cluster analysis and linear discriminant analysis) were performed. It is concluded that theHizikia fusiforme samples contained the highest values of total and inorganic As and thatmost Cd concentrations exceeded the French Legislation. The two harvesting areas (Atlantic andPacific oceans) were differentiated using both univariate studies (for Cu, total As, Hg and Zn)and a multivariate discriminant function (which includes Zn, Cu and Pb).

© 2008 Elsevier B.V. All rights reserved.

Keywords:Marine algaeEdible seaweedHeavy metalsSpainPattern recognition

1. Introduction

Asian cultures have traditionally employed seaweeds(macroalgae) as a natural source of food and medicines, andJapan, Korea, China, Vietnam, Indonesia and Taiwan are by farthe largest consumers (FAO, 2002). Six million tons of freshalgae are now cultivated per year worldwide, amounting toaround 90% of the commercial demand (FAO, 2002).

In addition to the general use of algae extracts as additivesand intermediate food products, direct consumption has been

34 986498626.da), andrade@udc.ese),

All rights reserved.

steadily growing since the early 1980s (Hou and Yan, 1998),particularly in western countries, which had formerly beenreluctant to eat seaweed. Consumers in most developedcountries are turning to more natural and nutritional productssuch as seaweed-based products, many of which have unri-valled healthy properties (Netten et al., 2000). It is nowpossibleto find out a large variety of products derived from macro andmicroalgae throughout Spain and a huge increase in consump-tion is expected in the next few years (Ortega-Calvo et al.,1993).

Seaweeds are harvested and cultivated inwestern countriesmostly to extract agar, carrageenans and alginates (known ashydrocolloids or phycocolloids) (Radmer, 1996). Hydrocolloidshave attained commercial significance because they are used invarious industries, particularly food production. However,many seaweeds are consumed directly after only minor pre-processing (mostly drying). Red algae (mainly, Porphyra,commercial name ‘Nori’) are consumed frequently since they

306 V. Besada et al. / Journal of Marine Systems 75 (2009) 305–313

are rich in proteins and vitamins B and C. Among brown algae,Laminaria (generic commercial name, ‘Kombu’, withmore than12 species), Undaria (generic name ‘Wakame’) and Hizikiafusiforme (generic name ‘Hiziki’ ) are the most consumed.

Unfortunately, some seaweeds exhibit a high affinity forheavymetals (Bryan andHummerstone,1973) and, indeed, theyhave been used as biomonitors for metal pollution in estuarineand coastal waters worldwide and to evaluate the quality oftheir surrounding environment (Chmielewská and Medved,2001; Topcuoglu et al., 2001; Villares et al., 2005; Melville andPulkownik, 2006). However, heavy metal concentrations inalgae are strongly dependent on the environmental parametersof the sampling sites (salinity, temperature, pH, light, nutrientconcentrations, oxygen, etc) (Zbikowski et al., 2006) and on thestructural differences among the algae (Favero et al., 1996).

We have found few studies of the life-cycle of the seaweedsconsidered in this study, their physiological behaviour, theirelement accumulation patterns, and how the geochemicalprocesses involved in the uptakeof different elements affect theaccumulation of particular metals. Without doubt, there are agreat deal of research opportunities in thesefields (Brown et al.,1999). Furthermore, these parameters are strongly dependenton the particular seaweed, so extrapolations cannot be madefrom other species. Nevertheless, some general ideas can begiven in this introductory section and more specific commentsare included in the Results and discussion section.

The capacity of algae to accumulate metals depends on avariety of factors, the two most relevant ones being thebioavailability of metals in the surrounding water and theuptake capacity of the algae (Sanchez-Rodriguez et al., 2001).Uptake is currently considered to take place in two ways. Thefirst is a surface reaction in which metals are absorbed by algalsurfaces through electrostatic attraction to negatives sites. Thisis independent of factors influencing metabolism such astemperature, light, pH or age of the plant, but it is influencedby the relative abundanceof elements in the surroundingwater.This seems tobe themainuptakemechanism for Zn. The secondis a slower active uptake in which metal ions are transportedacross the cell membrane into the cytoplasm. This form ofuptake is more dependent upon metabolic processes (it seemsto be the relevant one for Cu, Mn, Se and Ni), and it is subject tovariations due to changes in temperature, light, or age of theplant (Sanchez-Rodriguez et al., 2001).

It is alsoworth noting that physiological changes and growthcan affect concentrations of metals in the macroalgal tissue(Huerta-Diaz et al., 2007). The concentrations are generally lowin summer when growth rates are high and the accumulatedmetals are diluted, and high in winter when the metabolicprocesses slowdown (Brix and Lyngby,1983; Hou andYan,1998;Villares et al., 2002, cited in Zbikowski et al., 2006).

The concentrations of Mn, Cu, Zn and Ni may be controlledby enzyme cofactors, and concentrations of Zn may also becontrolled by activators of dehydrogenases and protein-synth-esis enzymes. Fe, Cu and Znmay also accumulate in algal tissue(Lobban and Harrison, 1994, cited in Huerta-Diaz et al., 2007).Furthermore, the mobilisation of metals from the sediment inareas covered by large amounts of macroalgae could contributeto their accumulation. Some species are able to absorb elementsdirectly from sediment (through the roots, in which metalconcentrations are much higher than in the water column)(Zbikowski et al., 2006).

Oneof the seaweeds considered in thepresent study, Ulva, isan opportunistic alga that grows quickly under favourableconditions, and this may cause rapid dilution of elements in itstissues (Villares et al., 2005). However, seasonal fluctuations inmetal concentrations in Ulva rigida have been attributed togrowth, age of tissue and abiotic factors (salinity and tempera-ture), as well as to variations in metal concentrations in theenvironment (Villares et al., 2002). Also, because of the laminarstructure of Ulva lactuca (with a relatively high surface area), itmainly takes up solubilised metals (Villares et al., 2001).

In general, green algae have a lowermetal-binding capacitythan brown algae (Schiewer andWong,1999) and the latter areapparently unable to regulate the uptake of trace elements dueto the presence in their cell walls of a large number ofcompounds (e.g. alginic acid and proteins).

Surprisingly, there is little legislation on seaweeds in theEuropean Union, so little control is exercised on potentiallyharmfulmetals. Francewas the first European country to set upregulations on the use of seaweeds for human consumption asnon-traditional foods. Currently 12 macroalgae and 2 micro-algae are authorised as vegetables and dressings/flavourings(Burtin, 2003). French limits for edible seaweeds are: Pbb5mg/kg dry weight (mg/kg d.w.); Cdb0.5 mg/kg d.w.; Hgb0.1 mg/kgd.w.; and inorganic Asb3 mg/kg d.w.

At present, neither Spain nor the European Union (EU) hasspecific legislation on this subject. The EU Regulation for Pb, Cdand Hg in foodstuffs (European Commission, 2006) does notconsider algae, and efforts are currently being made by aCommittee of Experts within the European Commission, the“Industrial Contaminants” working group, to decide whethergeneral advice or a special regulation should be issued. The onlySpanish legislation concerns seaweeds for animal consumptionand states that inorganic As should be less than 2 mg/kg d.w.and that special care should be devoted to Hizikia fusiforme(BOE, 2004). A very recent paper (Nakajima et al., 2006) alsodemonstrated that Hiziki ingestion can be considered equiva-lent to As(III) intake from polluted water as the urinary arseniclevel of volunteers was close to that of individuals withhyperkeratosis and hyperpigmentation in regions endemic forarsenic poisoning; accordingly, long-term ingestion of Hizikimight cause arsenic poising.

To the best of our knowledge only a very small number ofpapers analysing heavy metals in edible algae have beenpublished (they will be referred to hereinafter), and this iscurrently an emerging field. There is also a need to compare themetal content in algae fromdifferent production areas. The aimof this work is therefore to provide information on theconcentrations of several harmful heavy metals present incommercialised seaweed samples. This may contribute tocurrent discussions on issuing joint quality controls on seaweedquality within the European Union and help to determinewhether seaweeds can be differentiated objectively by employ-ing chemical measurements.

2. Materials and methods

2.1. Samples

Samples were obtained from specialist shops throughoutSpain.Mostof themcontainedonlyone type of seaweed thoughsomeweremixtures of different algae (termed ‘salads’). Several

Table 1Comparison between experimental results and certified values for two CRMs(mg/kg dry weight)

Element CRM 279 CRM 60

Certified Measured Certified Measured

Cadmium 0.274±0.022 0.271±0.017 2.20±0.10 2.29±0.17Lead 13.48±0.36 13.43±2.15 63.8±3.2 64.7±4.6Mercury 0.041–0.054⁎ 0.049±0.016 0.34±0.04 0.37±0.04Copper 13.14±0.37 13.46±0.78 51.2±1.9 49.9±2.9Zinc 51.3±1.2 50.4±2.5 313±8 333±7Total Arsenic 3.09±0.20 3.22±0.81 8⁎ 7.77±2.08

⁎Indicative value.

307V. Besada et al. / Journal of Marine Systems 75 (2009) 305–313

samples of a unique seaweed were provided by a Spanish firmspecialised in growing/harvesting and marketing seaweed.Efforts were made to acquire as many different samples(‘species’) as possible from both the Atlantic and Pacific Oceansand cover most commercially available options. In addition,some agar samples were included in this study because of theirwidespread use in foods (e.g. as thickening agents in meatproducts and desserts).

In total, 52 seaweed samples were analysed in this study:agar (Gelidium spp.); arame (Eisenia bicyclis); seaweedspaghetti (Himanthalia elongata); hiziki (Hizikia fusiforme);kombu (Laminaria spp); sea lettuce (Ulva rigida); Irish moss(Chondrus crispus); nori (Porphyra umbilicales) and wakame(Undaria pinnatifida). In addition, two seaweed ‘salads’ werefound, one composed of a mixture of wakame, ogonori,kombu, agar and akamodoki (algae salad number 10) andthe other of wakame, nori and sea lettuce (seaweed saladnumber 11). All sampleswere dried, ground and homogenisedin the laboratory prior to analysis.

2.2. Analytical measurements

The treated samples of around 1 g wereweighed and placedin a Teflon reactor fitted to a stainless steel container (measure-ment of inorganic As required only 0.5 g). After addition of 1mLof ultrapurewater (Milli-Q, Millipore) and 6mL of concentratednitric acid (Merck, Suprapur), the reactor was set to 90 °C for 2 hand then to 130 °C for 4 h. The digested sample was transferredto a volumetric flask and made up to 25 mL with Milli-Q water.

Quantification was performed using a Perkin-Elmer AAna-lyst 800 spectrophotometer, equipped with a Zeeman back-ground correction device (Cu and Zn by flame AAS; Cd, Pb andtotal As by electrothermal AAS). The operational parametersand matrix modifiers were those recommended by themanufacturer. Total Hg was determined by the cold vapourtechnique, employing a Perkin-Elmer FIMS-400 system (SnCl2as reducing agent). Determination of inorganic As includedsolubilisationwith hydrochloric acid, reduction and subsequentextractionwith chloroform, back-extraction into diluted hydro-chloric acid, dry-ashing, and quantification by hydride genera-tion AAS employing a Perkin-Elmer FIAS 200 device (Muñozet al., 1999a). The detection limits expressed in mg/kg dryweight were Pb: 0.008; Cd: 0.005; Hg: 0.001; Cu: 0.2; Zn: 1;total As: 0.050; and inorganic As: 0.020.

All analytical protocols were included in a quality controlsystem,which included analysis of certified referencematerials,duplicated samples, procedural blanks and international inter-laboratory exercises such as those from QUASIMEME and IAEAon a regular basis (Wyse et al., 2003; Quasimeme, 2004).

Table 1 shows the analytical results (mean±SD) for eightindependent analyses of two certified reference materials: asea lettuce, Ulva lactuca (CRM 279) and an aquatic plant, La-garosiphon major (CRM 60), both from the EU CommunityBureau of Reference. It is seen that the results agreed with thecertified ones.

Due to theabsence of certified (or guide) values for inorganicAs in the CRMs available for different organic matrices, a seaorganism (the dogfish muscle, Squalus acanthias, NationalResearch Council of Canada, DORM-2 CRM) was selected to“validate” the protocol for measuring inorganic As. This CRMhad previously been analysed byMuñoz et al. (1999a,b), also for

inorganic As andwith the samemethodology as that employedhere. These authors worked with samples whose inorganic Ascontents were in the same range as the seaweeds studied here.These were therefore the only published data we could find toevaluate the trueness of the analytical methodology. Ourresults, 0.136±0.007mg/kg d.w. (mean±SD for six independentanalyses), agreed with those of Muñoz et al. (1999b), i.e. 0.145±0.011mg/kg d.w., and this supported a satisfactory performanceof the method. In addition, in recovery studies carried out byspiking aliquots of the reference materials, the averagerecoveries were: 98.9% for Cd , 99.6% for Pb, 105.1% for Hg,102.4% for Cu, 98.2% for Zn and 104.2% for total As (using theCRM 279). For CRM 60, the values were: 104.1%, 101.4%, 108.8%,97.5%, 106.4% and 97.1% for Cd, Pb, Hg, Cu, Zn and total As,respectively. Recovery for inorganic As was 93.8%.

2.3. Statistical analysis

All studies were performed using Statgraphics v5Plus andSPSS v11; all tests were performed at a 95% confidence level,unless otherwise stated.

3. Results and discussion

The experimental concentrations are summarised inTable 2.Although the determination of inorganic elements in variousalgae in different countries has been summarised elsewhere(Hou and Yan, 1998), it is difficult to compare results fromvarious authors because of differences in sample treatmentsand analytical procedures. Furthermore, several studies attrib-uted seasonal variations in themetal concentrations to the algalgrowth rate. For instance, concentrations decreased in macro-algae during growing periods and increased during the winterdormant period (Phillips, 1994), the possible causes for whichincluded allometric parameters (influencing metal uptake andaccumulation), environmental factors (affecting metal accu-mulation, Brown et al., 1999), and local variation in salinity(affecting biological uptake, Netten et al., 2000).

Here, a preliminary univariate study was performed con-sidering all samples and elements. Then, multivariate studiesaddressed whether the heavy metals studied differentiateseaweeds according to their type and/or geographical origin.

3.1. Univariate studies

3.1.1. CadmiumTable 2 shows that Cd concentrations for different seaweeds

are highly variable. The relationship between heavymetals and

Table 2Concentrations found for several edible seaweeds (mg/kg dry weight)

Species Commercial name Graphicalcode

Cd Pb⁎ Hg Cu Zn As⁎ Inorganic As

Gelidium spp. Agar 1 0.025–0.046 0.381–0.861 0.005–0.009 0.410–1.55 1.30–6.29 b0.05–0.21 0.025–0.135Eisenia bicyclis Arame 2 0.585–0.827 0.029–0.096 0.023–0.047 3.06–4.54 21.4–23.5 27.9–34.1 0.041–0.170Himanthalia elongate Seaweed spaghetti 3 0.310–0.326 0.203–0.259 0.008–0.016 1.14–1.25 48.5–48.7 32.9–36.7 0.166–0.245Hizikia fusiforme Hiziki 4 0.988–2.50 b0.008–0.531 0.015–0.050 1.78–7.70 4.72–19.5 103–147 32.1–69.5Laminaria spp Kombu 5 0.085–1.83 b0.008–0.460 0.001–0.005 0.91–2.50 10.3–23.2 51.7–68.3 0.052–0.443Ulva rigida Sea lettuce 6 0.031–0.033 1.00–1.05 0.018–0.019 3.05–3.15 5.61–6.14 6.41–7.06 0.151–0.177Chondrus crispus Irish moss 7 0.718–0.742 0.403–0.726 0.006–0.007 1.55–2.21 51.8–53.3 23.2–25.5 0.217–0.225Porphyra umbilicales Nori 8 0.253–3.10 b0.008–0.270 0.008–0.032 5.50–14.1 39.5–73.8 28.9–49.5 0.132–0.338Undaria pinnatifida Wakame 9 0.267–4.82 b0.008–1.28 0.010–0.057 1.07–1.70 8.25–26.6 42.1–76.9 0.045–0.346Wakame, ogonori, kombu,

agar and akamodokiAlgae salad 10 1.69–1.80 0.189–0.420 0.024–0.035 1.47–1.56 42.8–43.4 18.6–19.1 0.240–0.283

Wakame, nori andsea lettuce

Seaweed salad 11 0.683–0.709 1.31–1.35 0.006–0.017 7.00–7.08 26.2–27.00 19.7–23.0 0.117–0.223

⁎The symbol ‘b’ means lower than the limit of detection (stated value).The graphical codes correspond to those in the plots.

308 V. Besada et al. / Journal of Marine Systems 75 (2009) 305–313

algae ‘classified’ by their colour (Chlorophyceae, green; Phaeo-phyceae, brown; and Rhodophyceae, red) has been discussed bydifferent authors. Topcuoglu et al. (2001) found that Cdconcentrations were higher in red algae (Pterocladia capillacea,mean 1.40mg/kg d.w.) than in brown (Cystoseira barbata, mean0.55 mg/kg d.w.) and green algae samples (Ulva lactuca,0.50 mg/kg d.w.).

On the other hand, in the present work the highest Cdconcentration (4.8 mg/kg d.w.) corresponded to brown algae(wakame) (since none of Topcuoglu's seaweeds were availablein the Spanish samples, comparison is not straightforward). Awakame batch from the Atlantic Ocean had a much higherconcentration (4.8 mg/kg d.w.) than any other value reportedpreviously: 1.9 and 0.71 mg/kg d.w. from Almela et al. (2002)and Netten et al. (2000), respectively. Nevertheless, two otherwakame batches, also from the Atlantic Ocean, had very lowvalues (ca. 0.3 mg/kg d.w.). It is noteworthy that the widestconcentration ranges corresponded to Porphyra umbilicales andUndaria pinnatifida (nori and wakame, respectively).

A two-wayAnovawas carried out considering ‘seaweed‘ and‘ocean’ asmain factors. Table3 shows that the average values forboth the Atlantic and Pacific Oceans were comparable. Resultsfor the Atlantic region were more disperse than those for thePacific Ocean. The ‘species’ factor was not statisticallysignificant.

Considering the French Legislation as a working reference(Almela et al., 2002) , arame (Eisenia bicyclis), hiziki (Hizikiafusiforme), Irish moss (Chondrus crispus), wakame (Undaria

Table 3Summary of main statistics and two-way ANOVA results (95% confidence)

Cd Pb Hg

Mean 1.07 0.30 0.018SD 1.19 0.38 0.013Max 4.82 1.35 0.057Min 0.025 b0.008 0.001

2-way ANOVA (p-values)Seaweeds 0.2044 0.0003 0.0000Region 0.5500 0.0850 0.0136

pinnatifida from the Pacific region), algae salad and seaweedsalad exceeded the 0.5 mg/kg d.w. limit. Up to 50% of thesamples of kombu and nori (Laminaria spp., from the Pacificregion, and Porphyra umbilicalis, from the Atlantic region)exceeded the French limit. The same occurred for one third ofthe Undaria pinnatifida (wakame) samples from the Atlanticregion.

3.1.2. LeadSeveral samples of different algae (Table 2) had concentra-

tions below the method limit of detection. The highest values(1.35 mg/kg d.w.) corresponded to the seaweed salad from theAtlantic region. This was not surprising because the twocomponents were analysed separately and yielded highconcentrations: 1.05 mg/kg d.w. for sea lettuce, and 1.28 mg/kg d.w forwakame. Levels for Pbwere similar to those found byother authors (Almela et al., 2002; Topcuoglu et al., 2003)although lower than those from the Black Sea (Topcuoglu et al.,2001). It isworth noting that batches of the same seaweed fromdifferent locations had different Pb levels.

An Anova study showed comparability among the averagevalues of the two main harvesting regions (Pacific and AtlanticOceans, Table 3). Nevertheless, the highest figures corre-sponded to the Atlantic region, and particularly to the seaweedsalad and a wakame sample. Note that the confidence intervalfor Pb in seaweed saladoverlappedonlywith that for sea lettuceand that both species were from the Atlantic region (Fig.1). Theaverage value for all wakame samples was comparable to those

Cu Zn As inorg As

3.79 29.37 46.95 6.023.43 21.48 33.97 16.85

14.1 73.8 147 69.50.41 1.30 b0.05 0.025

0.0000 0.0000 0.0000 0.00000.0010 0.0120 0.0146 0.9813

Fig. 1. Graphical effect of ‘seaweeds’ on the average results (two-way ANOVA) of trace metals (average values and confidence intervals calculated using the leastsignificant difference, 95% confidence). Codes: agar=1, arame=2, seaweed spaghetti=3, hiziki=4, kombu=5, sea lettuce=6, Irish moss=7, nori=8, wakame=9,algae salad=10, seaweed salad=11.

309V. Besada et al. / Journal of Marine Systems 75 (2009) 305–313

from other algae (but not sea lettuce and seaweed salad). Allexperimental values werewell below the French limit (5mg/kgd.w.).

3.1.3. MercuryIn general, values for total Hg (0.001–0.057mg/kg d.w.) were

highly similar to those reported previously (Netten et al., 2000;Almela et al., 2002) and clearly lower than the French limit of0.1 mg/kg d.w. (Almela et al., 2002). The two-way ANOVAshowed that the average values for the two regions weredifferent (Atlantic, 0.021mg/kgd.w. vs. Pacific, 0.012mg/kgd.w.),see Table 3. For the seaweed factor, arame (Eisenia bicyclis), hiziki(Hizikia fusiforme), wakame (Undaria pinnatifida) and the algaesalad showedhigher average values than other seaweeds (Fig.1).

3.1.4. CopperCu concentrationswere similar to those reported elsewhere

(Netten et al., 2000; Topcluogu et al., 2003). The Atlantic andPacific regions had different average values (2.14 mg/kg d.w.and 4.45 mg/kg d.w., respectively). Four nori samples out of 12had huge values (14.1 mg/kg d.w.), thus affecting the compar-ison. After discarding them, the average values for the tworegions overlapped. The Anova study (see Table 3 and Fig. 1)

revealed significant differences between nori plus seaweedsalad and all other algae.

3.1.5. ZincAs for the abovemetals, the experimental values for Znwere

similar to those from other studies (Hou and Yan, 1998; Nettenet al., 2000), and very disperse. The two-way ANOVA showedthat there were differences between harvesting regions andbetween seaweeds (Table 3). The Atlantic average (30.9 mg/kgd.w.) was greater than the Pacific average (ca. 24.5 mg/kg d.w.).

Seaweeds showed three concentration levels (Fig. 1). Onecorresponded to agarand sea lettuce (lowest values, ca. 3mg/kgd.w.), the second to arame, hiziki, kombuand the seaweed salad(intermediate values), and the third to seaweed spaghetti, Irishmoss, nori and algae salad (highest levels, N45 mg/kg d.w.).Within the last group, seaweed spaghetti and Irish moss camefrom the Atlantic Ocean, while the algae salad came from thePacific region. Porphyra umbilicales (nori) was present in bothOceans and the corresponding samples showed no statisticallysignificant differences (though the Atlantic samples showedsomewhat higher values).

Finally, it is worth noting that Zn concentrations for Ulvalactuca were reported to vary seasonally (Brown et al., 1999),

Fig. 2. Varimax PC1-PC2 scores subspace considering autoscaled data and allthe species. Codes: agar=1, hiziki=4, sea lettuce=6, nori=8.

310 V. Besada et al. / Journal of Marine Systems 75 (2009) 305–313

with higher figures in winter than in spring or summer. Theauthors concluded that these results highlight the complexityof the inter-relationships between metabolism, growth rateand metal uptake, for which there has been no adequateexplanation for most seaweed species and metals. Further-more, it was also reported that some algae, such as wakame,appeared to uptake some elements (including Zn) accordingto their growing stage (Netten et al., 2000).

3.1.6. Total and inorganic arsenicIn general, As concentrations are higher in marine organ-

isms than in terrestrial ones (Phillips, 1990) and this explainswhy seafood has higher As contents than other foods.Accordingly, the total amount of As ingested by humansdepends greatly on the amount of seafood included in theirdiet. It is well-known that organic and inorganic species of Asdiffer widely in their toxicity (Oygard et al., 1999), inorganicforms being in general more toxic than organic ones (Lópezet al., 1994). Algae accumulate As, and hence play an importantrole in its cycle. Macroalgae accumulate moderate amounts oftotal As, and the concentrations are higher in brown algae thanin green and red ones (Phillips, 1990). This suggests that theaccumulation ratios are more heavily dependent on theparticular seaweed than on the environmental level of As. The‘Mixed Commission of the Codex Alimentarius' (Food andAgriculture Organisation-World Health Organisation, FAO-WHO) recommended measuring not only the total concentra-tion of As present in food, but also the concentrations ofinorganic As (Tsuda et al.,1992), as it could happen that seafoodexhibiting very high concentrations of total As have no toxicitybecause most of the As is in its organic forms.

Our experimental results revealed that total As for wakame,arame and nori were comparable to other reports, althoughvalues for hiziki and kombu were slightly higher (Netten et al.,2000). Furthermore, our results strongly agreed with those ofAlmela et al. (2002). The average values for the differentseaweeds were not comparable. The largest difference wascaused by the hiziki samples (Hizikia fusiforme showed thehighest figures, at 103–147 mg/kg d.w.). They also caused theaverage of the Pacific Ocean to be significantly higher than thatof the Atlantic region. A two-way ANOVA (hiziki samplesexcluded) revealed that theAtlantic averagewas larger than thePacific one. Kombu (Laminaria) andwakame (Undaria) had totalAs concentrations of around 60 mg/kg d.w., and agar and sealettuce had the lowest values (b7 mg/kg d.w.).

For inorganic As, the values were similar to those foundelsewhere (Almela et al., 2002; Agency, 2004; Nakajima et al.,2006). Nevertheless, as the high fibre content in algae mayaffect inorganicAs bioavailability (Vélez andMontoro, 2001), nodirect conclusions can be drawn from the analytical data alone.

Remarkably, all Hiziki samples exceeded the French limit(=3.0 mg/kg d.w.), and in fact Hizikia fusiforme is not includedwithin the 12 macroalgae authorised for human consumption(Burtin, 2003). Here, we found levels of inorganic As of 70 mg/kg d.w. for Hizikia fusiforme. In July 2004 the British FoodStandard Agency advised people not to eat this brown algaebecause of its levels of inorganic As (Agency, 2004). Morerecently, Nakajima et al. (2006) demonstrated that Hizikiingestion might lead to undesired consequences because of itsAs contents. After discarding the Hiziki samples no statisticaldifferences were found for the remaining seaweeds (see Fig. 1).

3.2. Multivariate analysis

3.2.1. Principal component analysisA Varimax principal components analysis (PCA) yielded

three PCs,whichexplained ca73.3%of thevariance. PC1 (33.53%of the variance) was clearly associated with total As andinorganic As, which characterised theHizikia fusiforme samples(Fig. 2). PC2 (22.54%of the variance)wasmostly associatedwithCu and Zn, which differentiated Porphyra umbilicales (nori)from other seaweeds (PC2-scores N0.9 denote Porphyrasamples). Since both Cu and Zn dominated this factor, theyshouldhave a commonorigin,whichhasusually been related tourban effluents (Villares et al., 2002).

Two other algae were discriminated further: agar and sealettuce (Fig. 2). The former had the lowest As (total andinorganic), Cu and Zn concentrations among all the samples.The latter also had low values but higher than those for agar.PC3 (17.24% of the information) was associated mainly with Cdand Pb (which had an inverse relationship). This PC was notuseful for differentiating among seaweeds. It is noteworthy thatthe PCA was not sensitive to the geographical regions fromwhich the samples came.

3.2.2. Cluster analysisThe best results for cluster analysis were found by employ-

ing autoscaled data, the Ward grouping method and the cityblock (or Manhattan) distance (suited to handling largedifferences in the concentrations of the metals in the samples).As expected, the dendrogram (Fig. 3) confirmed the mainresults obtained from both the PCA and the ANOVAS.

Five sample groupswere observed:GroupA, associatedonlywith hiziki samples (with high total and inorganic As); Group B,associated with the nori samples (with high Cu and Zn values);Group C, clustering duplicated samples for seaweed spaghetti,Irish moss and algae salad; Group E, clustering agar, sea lettuceand seaweed salad (all with the lowest values in most metals),and also including a duplicated sample of wakame, showingvery low values compared to its counterpart; and Group D,which was a mixture of different samples without a clearexplanation except for their metal content (the subgroups didnot correspond to specific algae).

Fig. 3. Dendrogram obtained using autoscaled data, the Ward groupingmethod and the city block distance. Codes: agar=1, arame=2, seaweedspaghetti=3, hiziki=4, kombu=5, sea lettuce=6, Irish moss=7, nori=8,wakame=9, algae salad=10, seaweed salad=11.

Table 4Contingency table for the LDA discrimination models (harvesting areas,Atlantic=1, Pacific=2)

Predicted (⁎) Predicted (⁎⁎) Theoretical

1 2 1 2 1 2

Real 1 18 (18) 8 (8) 13 (18) 13 (8) 26 –

2 3 (3) 23(23) 5 (4) 21 (22) – 26

⁎Considering all metals.⁎⁎Considering only metals that showed discrimination capabilities afterindividual ANOVAS—see text for details.The values between brackets correspond to forward inclusion of variables.

Fig. 4. Box-Whisker representation of the classification functions obtained byLDA (forward selection) obtained for each harvesting area: 1 characterisesthe Atlantic ocean (= −4.30+6.09⁎Pb+0.16⁎Zn −0.35⁎Cu), whereas 2characterises the Pacific Ocean (= −1.64+1.75⁎Pb+0.17⁎Cu+0.04⁎Zn). Seetext for more details.

311V. Besada et al. / Journal of Marine Systems 75 (2009) 305–313

3.2.3. Linear discriminant analysisThe fact that neither PCA nor hierchical clustering differ-

entiated among the two harvesting areas indicated that theoverall variance was dominated by the inherent differencesbetween the seaweeds. Nevertheless, since some of the metals(total As, Cu, Hg and Zn) revealed different averages for theharvesting areas when two-way ANOVAS were performed, amultivariate discrimination technique, linear discriminantanalysis (LDA), was applied. LDA searches for discriminantfunctions (linear combinations of the experimental variables)that discriminate as much as possible among the groupsdefined by the scientists, in this case the two geographicalorigins. Note that PCA and cluster analysis extract patternswhichexplainmostof thevarianceof thedataset, although theydonot necessarily differentiatewell between the groups.On theother hand, LDA looks for discriminant functions capable ofdifferentiating the groups as much as possible, even if thesefactors fail to explain most of the variance. Therefore, they arecomplementary techniques and are not redundant.

Studies were carried out considering first all metals andthen only those that showed some discrimination capabilitiesin theANOVA studies (total As, Cu,HgandZn). Furthermore, theforward approach was also applied as a way to consider onlythose metals that statistically improved the overall discrimina-tion capability of the model.

Consideration of total As, Cu, Hg and Zn yielded a 75%classification success when all samples were used for training,but only a 65% success when leave-one-out cross-validation(LOOCV) was used. The forward approach included only Cu andZn in the model, leading to approximately 81 and 77% successratios for all samples in themodel and LOOCV, respectively (seeTable 4).

Slightly better results were obtained considering all metals.The discriminant function (standardised coefficients) was1.17⁎Zn+0.94⁎Pb+0.48⁎As+0.094⁎Hg+0.073⁎Cd−0.59⁎As(inorg)−0.86⁎Cu,which allowed for 86 and 78.8% success ratios(all samples in themodel and LOOCV, respectively; see Table 4).The forward approach yielded the 1.29⁎Zn+0.85⁎Pb−1.00⁎Cufunction (standardised coefficients), with 78.8% success in bothcases. This latter option was preferred because it used fewermetals (i.e. it included less random variability) and because the

classification ratios considering all samples and cross-valida-tion (which simulate classification of truly unknowns) werealmost the same. It is noteworthy that Pb increased the successratios. Though Pb itself did not differentiate the two regions, itcorrelated positively with Zn and Cu and accordingly theinformation it added to the discriminant function improved itsclassification ability. The classification functions were: AtlanticOcean=−4.30+6.09⁎Pb+0.16⁎Zn−0.35⁎Cu, and Pacific Ocean=−1.64+1.75⁎Pb+0.17⁎Cu+0.04⁎Zn (note that Znwas not criticalfor the Pacific region and that Pb played an important role in theAtlantic area).

Fig. 4 shows the classification scores. It is worth noting thattwo agar samples were always misclassified, regardless of themodel. As explained above for PCA, they had very low values inmost variables (but medium Zn levels) and although they werefrom the Atlantic ocean, they were classified as being from thePacific area. One nori sample was also misclassified as beingfrom the Pacific, probably because of its high total and inorganicAs concentrations. Two algae salads (#49 and #50 in the figure)were wrongly considered as being from the Atlantic (probablybecause they contained wakame, which had very highconcentrations of several metals).

312 V. Besada et al. / Journal of Marine Systems 75 (2009) 305–313

4. Conclusions

This study showed that there is a need for a national(Spanish)—or preferably European—regulation on the max-imum amount of pollutants in edible seaweeds commercia-lised for human consumption. Here several heavy metalswere measured in different commercial products. Accordingto the limits laid down by the recent French legislation, thealgae studied scored as follows:

(i) Most samples exceeded the limits set for cadmium.(ii) Hizikia fusiforme showed the largest total and inorganic

As concentrations, in all cases exceeding the inorganicAs limit (which would preclude its consumption byhumans).

(iii) The results for Hg and Pd were well below the limits.(iv) Four nori (Porphyra) samples and the salads showed

the highest Zn and Cu concentrations (around 8–14and N45mg/kg d.w., respectively). The content of thesemetals is not covered by the French legislation.

The average metal concentrations for seaweeds from thetwo production areas (Atlantic and Pacific oceans) were similarand could not be differentiated by either PCAor cluster analysis.Nevertheless, two-wayANOVA studies showed that total As, Cu,Hg and Zn yielded statistical differences (95% confidence).Accordingly, multivariate LDA studies were made, whichsatisfactorily classified the samples as a function of theirgeographical origin, with ca. 80% classification success. Despitethis, more studies seem necessary in order to clearly differ-entiate between the inherent variability of thedifferent types ofseaweed and the variability caused by the region inwhich theyare grown. In our opinion, future studies should focus not onlyon increasing the data for different metals and different algaebut on investigating the ecology and life-history of the differentseaweeds, as well as on the processes governing metalaccumulation.

Acknowledgements

This work is a part of a broader study led by the InstitutoEspañol de Oceanografía (IEO, Vigo), and the Secretaría Generalde Pesca Marítima (SGPM), Spanish Government.

The authors would like to thank Juan Manuel Salinas (IEO,Santander) and Rosa María Mirás. Thanks are also due to thetechnicians of the IEO's Pollution Laboratory in Vigo.

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