Carmen Rubio

Angel Gutierrez

Antonio Burgos

Ángel Gutiérrez

Arturo Hardisson

Total dietary intake of mercury in the Canary Islands, Spain 1 2

Keywords: Metals -uptake, Metals analysis -AAS, Total diet studies, Toxicology Additives/Contaminants: Heavy metals -mercury Food Types: Fish and fish products, Meat, Organic foods, Vegetables Mercury, AAS-cold vapour, Dietary Intake, Canary Islands

Total dietary intake of mercury in the Canary Islands, Spain

Environmental contamination through heavy metals is a world-wide recognized 37 public health hazard. Among the different environmental sources of Hg, those of 38 industrial origin (chlorine-alkaline plants, paper factories, organic-mercurial 39 fungicides, gold purification processes) stand out as the most dangerous ones, 40 because in the areas destined to industrial spilling there can be found the 41 highest levels of Hg, almost all atmospheric and of great volatility (Hardisson, 42 1981;[START_REF] Kurasaki | Metals 356 in water in the Central Kalimantan, Indonesia[END_REF]. In Brazil, for example, gold mining activities, like 43

Manaus and Mato Grosso, provide a mercury dietary intake that is very close to 44 the upper limit set by WHO (Favaro et al., 1997). In a general population, 45 mercury dietary intake is mainly influenced by fish consumption (Wilhelm et al., 46 2005). The WHO International Programme on Chemical Safety established that, 47 during 1980-1988, the contribution of Hg from fishery products varied from 20 to 48 85% [START_REF] Galal-Gorchev | Dietary intake, levels in food and estimated intake of 332 lead, cadmium and mercury[END_REF]. Recently, the increased popularity of fish as a 49 source of dietary proteins and omega-3 fatty acids is expected to raise the risk 50 of methyl mercury induced health problems in the US population (Knobeloch et 51 al., 2006). 52

53

The presence of metals in marine sediments and some fish species and their 54 products is a consequence of both, natural and anthropogenic contamination 55 [START_REF] Herawati | Cadmium, copper, 343 and zinc levels in rice and soil Japan, Indonesia and China by soil tipe[END_REF][START_REF] Schuler | Mercury concentrations in 401 Louisiana and Chinese crayfish[END_REF]. Fish and crustaceans, due to their 56 high accumulation of Hg, are often used as indicators of this environmental 57 pollution. Even though an accumulation of mercury in liver for marine organisms 58 like dolphins, seals and porpoises has been reported by many researchers 59 [START_REF] Rodríguez-López | Elementos 388 tóxicos en alimentos, bebidas y envases[END_REF][START_REF] Vega | Niveles 422 de metilmercurio en pescados[END_REF], a recent study considered the 60 [START_REF] Coelho | Can Nassarius reticulatus be used as a bioindicator for Hg 302 contamination? Results from a longitudinal study of the Portuguese coastline[END_REF]. 62

63

In aquatic environments, inorganic Hg is microbiologically transformed into 64 methyl-mercury (MeHg), a toxic lipophilic organic compound. Consequently, 65 populations with a traditionally high dietary intake of food originating from either 66 fresh water or marine environments, like coastal population, show the highest 67 dietary exposures to mercury and methyl-mercury. The total Hg level is a 68 function of the methyl mercury content, and the Hg content in fish is mainly 69 MeHg. This is, for example, the case of the Adriatic Sea, where industrial 70 pollution has affected both total Hg and methyl-mercury content in seafood 71 [START_REF] Buzina | 288 Effect of industrial pollution on seafood content and dietary intake of total and 289 methyl-mercury[END_REF] as well as the Baffin Inuit living in the Canadian Artic (Chan 72 et al., 1995). Even in an industrially non-polluted area of the Adriatic Sea 73 [START_REF] Buzina | Dietary mercury intake and human exposure in an Adriatic population[END_REF] it has been observed that 20% of the consumers had a 74 total weekly dietary mercury intake above the PTWI. It has been calculated that 75 people consuming, more than 6 times/week, fish and other seafood products 76 absorb 300 µg of total mercury for every 1559 g of food and 200 µg of methyl-77 mercury, for every 1365g. In the Songhua River, China [START_REF] Lin | A study of hazard of methyl-mercury pollution in no.2 Songhua 362 River to fishermen's health[END_REF], 90% of the 78 mercury that has been measured in the fishermen's body is supposed to be 79 provided by polluted fish. Recent studies describe mercury poisonings in 80 Indonesia [START_REF] Kurasaki | Metals 356 in water in the Central Kalimantan, Indonesia[END_REF] and in India [START_REF] Ali | Mercury Bioaccumulation induces oxidative stress and toxicity to 267 submerged macrophyte Potamogeton crispus L. Bull[END_REF], where many 81 aquatic resources have been reported to be contaminated by this metal. 82 83 Environmental, dietary and occupational exposure to inorganic mercury may 84 cause both clinical and sub-clinical effects [START_REF] Soleo | Immunologic effects of exposure to low levels of inorganic mercury[END_REF] (especially on psycho-motor coordination), neuroendocrine and renal damage 87 and gastrointestinal toxicity. Daily intake of methyl mercury is significantly 88 correlated with hair mercury concentrations (Iwasaki et al., 2003). 89 90 It has been observed that total level of Hg in hair, in toenails and methyl-91 mercury in blood, often used as biomarkers of the human exposure to this 92 heavy metal, raise when total fish consumption increases (Yoshizawa et al., 93 2002;[START_REF] Bjornberg | Methyl mercury 274 exposure in Swedish women with high fish consumption[END_REF]. Moreover, a significant dose-effect relationship 94 has been associated with long-term exposure to low doses of organic mercury 95 from usual consumption of marine fish in Italy [START_REF] Carta | Neuroendocrine and neurobehavioral effects associated with 295 exposure to low doses of mercury from habitual consumption of marine fish[END_REF] In Canada, 96 [START_REF] Innis | Increased levels of mercury 346 associated with high fish intakes among children from Vancouver, Canada[END_REF], concluded that children from various population subgroups, 97 like Chinese, initially included in a population not considered at risk, had 98 increased risk levels of neurotoxicity caused by Hg exposure to fish. 99 100 A high Hg intake coming from non-fatty freshwater fish, its consequent Hg 101 accumulation in the body and the promotion of lipid peroxidation by mercury 102 have been associated with excessive risk of acute myocardial infarction and 103 with death from coronary heart disease in eastern Finnish men (Meltzer et al. 104 1994;[START_REF] Salonen | Intake of mercury from 397 fish, lipid peroxidation and the risk of myocardial infarction and coronary, 398 cardiovascular, and any death in eastern Finnish men[END_REF]. Although, a recent study has not found any 105 connection between total mercury exposure and the risk of coronary heart 106 disease, a slight relation cannot be ruled out (Yoshizawa et al., 2002). Taking into account that the population in the Canary Islands reaches 2.000.000 117 people and is distributed as follows: 10.477 in El Hierro, 85.252 in La Palma, 118 21.746 in La Gomera, 85.2945 in Tenerife, 80.7049 in Gran Canaria, 89.680

in 119

Fuerteventura and 12.3039 in Lanzarote, in the present work we make a study 120 on the estimated provision to the dietary intake of mercury through consumption 121 of fish, to know the contribution to tolerable provisional weekly intake of Hg in 122 our population. We have made a study of total intake of mercury, with bigger 123 toxicological importance of metil mercury. 124 125

Material and Methods 126 127

Samples: Sample preparation is a major concern in AAS as it basically governs 128 the analytical performance characteristics, namely, detection limit, accuracy, 129 precision, speed, throughput and cost [START_REF] Subramanian | Determination of metals in biofluids and tissues: 413 sample preparation methods for atomic spectroscopic techniques[END_REF]. In this study, 130 samples were randomly bought at five different points (shopping major areas 131 present in the Canary Islands, in the Islands with bigger groups of population 132 (Tenerife, Gran Canaria, La Palma, Lanzarote and Fuerteventura). Areas for 133 collection of simples were selected, because these where the places with higher 134 number of buyers and more variety of brands. [START_REF] Yuyama | Determination of various 329 nutrients and toxic elements in different Brazilian regional diets neutron 330 activation análisis[END_REF][START_REF] Llobet | 364 Biological monitoring of environmental pollution and human exposure to metals 365 in Tarragona, Spain. IV. Estimation of the dietary intake[END_REF][START_REF] Enca | Encuesta Nutricional de Canarias 1997-1998[END_REF]. The ENCA is a survey where food intake has 141 been estimated using a method of food consumption at an individual level. 142

Specifically, the ENCA used two twenty-four-hour recalls -administered in two 143 non consecutive days -and a comprehensive food frequency questionnaire of 144 77 food items. The survey considered ages between 6 and 75 years of 2.025 145 families. The number of analysed samples in each group was twenty, 146

Analytical methodology: Total mercury determination can be performed by 147 applying different analytical methods. However, the most widely used technique 148 is AAS -cold vapour atomic absorption spectrometry -due to its simplicity and 149 sensitivity [START_REF] Hardisson | Mercurio en especies marinas. Revisión 338 bibliográfica[END_REF]AOAC, 1990;[START_REF] Hardisson | Determination of 340 mercury in fish by Cold Vapor Atomic Absorption Spectrometry[END_REF]. 150

Reagents: Milli-Q deionised water, sulphuric, nitric and chloride Merck p.a. 151 acids, lumatom, stannous chloride in 10% HCl freshly prepared from a Fisher 152 product, certified ACS, NIST SRM 1577a bovine liver, mercury standard 153 solution 1.000 mg/L, Fisher, certified for EAA and Acationox detergent, 154 Sherwood, 2% solution for the washing of the whole glass labware. 155

Apparatus: Pye-Unicam SP-1900 atomic absorption spectrometer, equipped 156 with Hg hollow cathode lamp and Hg cold vapour system with 15 x 1 cm quartz 157 cells. The detection limit was fixed, as in previous studies of our research group, 158 at 0.0005 µg/g [START_REF] Hardisson | Determination of 340 mercury in fish by Cold Vapor Atomic Absorption Spectrometry[END_REF]. The instrumental conditions were set at 159 253.27 nm wavelength, 0.2 nm slit-width and 6 mA lamp current without 160 However, once the results of the recovery tests were compared with the 165 microwave oven digestion method, method b) was selected for the study. 166

Moreover, method b) was faster than method a). 167 Method a: From 0.5 to 3 g of homogenized material were introduced in 168 topaz coloured flasks and 10 mL H 2 SO 4 as well as HNO 3 mL were added 169 in cold conditions. The flasks were then, placed, for 10-18 hours, in a stove 170 at 40 ± 5 ºC, until total mineralization. Once cooled, degasified in an 171 ultrasound bath and filtered through Albet 240 paper, they were finally 172 adjusted at 100 mL volume with deionised water (19,20). 173 Method b: From 1 to 2 g of homogenized material were weighed on Teflon 174 pumps. Then, 4 mL HNO 3 and 2 mL H 2 SO 4 were added for the sample's 175 digestion in a microwave oven (60-150 psi) for 40 min. Later, the samples 176 were cooled in a fridge for 20-30 min and degasified in an ultrasound bath. 177 Finally, volumes were adjusted at 100 mL with deionised water. 178 Total mercury determination: volumes ranging from 10 to 50 mL of the problem 179 solution were added in the reaction flask. Deionised water was then added to 180 obtain 70 mL volumes. From 2 to 5 mL of stannous chloride in 10% HCl were 181 also added. When the air force pump was started and the spectrophotometer 182 lecture became stabilized, the absorption was recorded. In the same way, a 183 calibration plot with a linear range was prepared, with standards of 0.05, 0.10, 184 0.15, 0.20, 0.25 and 0.30 mg/L of mercury 185

Recovery Study: the recovery study with a certified material "NIST SRM 1577a 186 bovine liver" is shown and the accuracy of the method proved (table 1) (Díaz et 187 al., 1994;[START_REF] Hardisson | Determination of 340 mercury in fish by Cold Vapor Atomic Absorption Spectrometry[END_REF]. The recovery percentage obtained for the 188 process of digestion with microwave oven (sample treatment method b) was as 189 good as those obtained for sample treatment method a). 190 191

Results and discussion 192 193

Table 2 shows the mean total Hg contents and standard deviations measured 194 for the different food groups. Among the groups with detectable total Hg 195 concentrations, marine products showed the highest levels. There were eleven 196 food groups with non-detectable Hg concentrations (fat-oils, bakery, legumes, 197 fruits, nuts, vegetables, potatoes, sweets, alcoholic drinks, non-alcoholic 198 drinks). Foods with regulated Hg limits presented Hg levels under the legal 199 values, none of the fish samples went above the mercury maximum tolerance 200 limit fixed for fishery products by European Legislation (0.5 mg/kg). 201 202 To estimate the total Hg intake ( , 2000). Fishery products are the food group that contributes most to the 205 Hg intake (5.4 µg/day), being 95.8% of the total intake. These results coincide 206 with those obtained by other authors in other Spanish Regions (Schuchmacher 207 et al, 1994;[START_REF] Cuadrado | Lead, cadmium and 310 mercury contents in average Spanish market baskets diets from Galicia, 311 Valencia, Andalucía and Madrid[END_REF][START_REF] Llobet | 364 Biological monitoring of environmental pollution and human exposure to metals 365 in Tarragona, Spain. IV. Estimation of the dietary intake[END_REF] . 208

209

Comparing the intake of the population in the Canaries with the total Hg intake 210 calculated for the population of other Spanish Regions (Table 4), it can be 211 observed that the total Hg dietary intake in the Canary Islands is lower than in 212

Tarragona (Schumacher et al., 1994, Llobet et al., 1998), Andalucía, Madrid, 213 País Vasco and Galicia and almost the same as in Valencia and the last 214 estimation trends observed in Tarragona [START_REF] Moreiras | Estimation of the dietary intake of cadmium, lead, mercury, and arsenic 377 by the population of Santiago (Chile) using a Total Diet Study[END_REF]Cuadrado et al., 215 1995;[START_REF] Urieta | Food surveillance in the Basque Country 416 (Spain). II. Estimation of the dietary intake of organochlorine pesticides, heavy 417 metals, arsenic, aflatoxin M1, iron, and zinc through the Total Diet Study, 418 1990/91[END_REF][START_REF] Bocio | Human Exposure to metals through the 279 diet in Tarragona, Spain: temporal trend[END_REF] Because the nourishing habits of 216 every region are different and in the Canary community there is consumed food 217 that possess less concentration of mercury that in the mentioned communities 218 previously, due to the fact that these communities are more industrialized that 219 the Canary community. 220

221

Table 5 shows the Hg intakes in different international populations. Apart from 222 those in Greenland, Baffin Inuit and Canadian Artic populations, Hg dietary 223 intake from local marine food has traditionally exceeded the limit established by 224 FAO/WHO [START_REF] Chan | Assessment of 298 dietary exposure to trace metals in Baffin Inuit Food[END_REF][START_REF] Johansen | Lead, cadmium, mercury and 351 selenium intake by Greenlanders from local marine food[END_REF]. In table 5 it can be 225 observed that Hg intake in the Canary Islands is lower than in USA, Japan and 226 the United Kingdom and almost the same as in Germany [START_REF] Boudene | Toxicidad de los metales[END_REF] and227 Chile (Munoz et al., 2005). As happens in France [START_REF] Noel | Determination of several elements in 384 duplicate meals from catering establishments using closed vessel microwave 385 digestion with inductively coupled plasma mass spectrometry detection: 386 estimation of daily dietary intake[END_REF], Denmark 228 [START_REF] Bro | Intake of essential and toxic trace 285 elements in random sample of Danish men as determined by the duplicate 286 portion sampling technique[END_REF][START_REF] Larsen | Monitoring the content and intake of trace elements from food in 360 Denmark[END_REF]

  Nassarius reticulates) as a poor indicator of total Hg 61 contamination

  human intake of mercury comes from ingestion of marine foods, the 109 Spanish Health Ministry has established the obligation to control levels of 110 and imported fish and fishery products(Rodríguez-López et 111 al., 2001). In Europe, Hg concentrations in foods are ruled by the European 112 Regulation 466/2001 and its modification, 78/2005. The following tolerable 113 maximum limits have been established: 0.5 mg/kg for fishery products and fish 114 meat and 1.0 mg/kg for certain species like tuna fish, etc. 115 116

  background correction; PHAXE pressurized reactors; CEM MDS-2000 161 low pressure Teflon glasses (< 200 psi), Teflon PFA; 162 PENTA ultrasound bath. 163 Samples treatment: Two sample treatments a) and b) were used at first. 164

  The total diet has been divided 135 into groups (milk, cheese, yogurt, other dairy products, fish, eggs, red meat, 136 cold meat, viscera, poultry and rabbit, fats-oils, cereals, bakery, legumes, fruits, 137 nuts, vegetables, potatoes, sweets, alcoholic drinks, non-alcoholic drinks). 138These groups were those established in the latest Nutritional Survey, performed 139 at the Canaries, as the groups with highest consumption in this area between 140

	F o r
	P
	e
	e r
	R
	e
	v i e
	w
	O n l
	y
	7

Table 3 )

 3 , it was necessary to use the food 203 consumption data from the latest Nutritional Survey carried out in the Canaries 204

	(ENCA
	F o r
	P
	e
	e r
	R
	e
	v i e
	w
	O n l
	y
	10

Table 1 : Accuracy of the measured concentrations of mercury in NIST Standard Reference material (µg/g wet weight)

 1 and in the Netherlands(Van Dokkum et 229 contributing to the total Hg dietary intake in the Canary Islands. The Island with 255 the lowest fish consumption (La Palma) is also the one with lowest mercury 256 intake. On the other hand, the Island of Fuerteventura shows the highest 257

	F o r
	P
	e
	e r
	R
	e
	v i e
	w
	O n l
	y

Table 2 : Hg concentrations obtained for the different food groups

 2

		Foodstuff	[Hg] (µg/kg ww)	Foodstuff	[Hg] (µg/kg ww)
		Milk	0.25± 0.06	Cereals	0.437 ± 0.200
		Cheese	0.37 ± 0.15	Bakery	<0.001
		Yogourt	0.26 ± 0.06	Legumes	<0.001
		Dairy products	0.30 ± 0.12	Fruit	<0.001
		Fishery products	118.9 ± 115.5	Dried Fruits (nuts)	<0.001
		Eggs	0.45 ± 0.16	Vegetables	<0.001
		Red meat	0.54 ± 0.19	Potatoes	<0.001
		Cold Meat	1.45 ± 0.55	Sweets	<0.001
		Viscera	1.53 ± 0.63	Alcoholic drinks	<0.001
		Poultry and rabbit	0.39 ± 0.15	Non alcoholic drinks	<0.001
		Fats and oils	<0.001	Water	<0.001
	25	Detection limit= 0.0005 µg/g
	26
	27

Table 3 : Hg intake from the food groups with detectable

 3

	[ [ [ [Hg] ] ] ] µg/day in the Canary Islands.

http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk

Table 4 : Comparison of this study with results from other Spanish Communities

 4

	Spanish Community	Reference	Hg Intake (µg/day)
	Canary Islands	This study	5.69
	Madrid	Cuadrado et al., 1995	10
	Madrid	Moreiras et al., 1995	9.8
	Galicia	Cuadrado et al., 1995	9
	Galicia	Moreiras et al., 1995	8.7
	Valencia	Cuadrado et al., 1995; Moreiras et al., 1995	4
	Andalucía	Moreiras et al., 1995	12.8
	Andalucía	Cuadrado et al., 1995	13
	Cataluña (Tarragona)	Schuhmacher et al., 1994	16 (only fish)
	Cataluña (Tarragona)	Llobet et al., 1998	4.8
	Cataluña (Tarragona)
	Male adults	Llobet et al., 2003	21.2
	Cataluña (Tarragona)	Bocio et al., 2005	5.3
	Basque Country	Urieta et al., 1996	18
	Spain	Bosnir et al., 1999	7.26
	30
	31
	32
	33
	34
	35
	36

http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.ukFood Additives and Contaminants

Commission Regulation (EC) No 466/2001 of 8 March 2001 setting maximum

Acknowledgements 260

The authors acknowledge the financial support for this project from FUNCIS 261 (Fundación Canaria de Investigación y Salud). 262


Alison Colyer
email: a.colyer@csl.gov.uk

Roy Macarthur

Joy Lloyd

Hez Hird

Hiz Hird

A comparison of calibration methods for quantification of Basmati and non-Basmati rice using microsatellite analysis

Keywords: Microsatellite, Statistical analysis, Calibration Additives/Contaminants: Non-Basmati rice Food Types: Basmati rice microsatellite, Basmati, DNA, calibration

come

A comparison of calibration methods for quantifictation

of Basmati and non-Basmati rice using microsatellite analysis

A comparison of calibration methods for quantifictation of Basmati and non-Basmati rice using microsatellite analysis compared involved power regression, linear regression (with and without log 10 transformation) and hyperbolic regression of the ratio of Basmati to non-Basmati peak areas. Assessments were made using the error uncertainty, standard error at the agreed limit of adulteration and 95% confidence intervals for five example data sets. The linear regression of the ratio of peak areas onto the ratio of content proportions was found to give the most precise calibration and thus enhanced quantification of the level of adulteration of Basmati rice with non-Basmati rice.

Introduction

The consumption of Basmati rice has gained in popularity in recent years, particularly in the UK, which consumes 70% of the Basmati rice imported into the EU (approximately 155,000 tonnes/year). Its popularity stems from its unique characteristics, which include a popcorn-like fragrance and light fluffy grains on cooking. All rice varieties are closely related and only skilled technicians are able to use a variety of objective measures to distinguish varieties apart. However, varietal identification using DNA based analysis has been reported in the literature. The range of DNA based techniques includes random amplified polymorphic DNA [START_REF] Ko | Random amplified polymorphic DNA analysis of Australian rice (Oryza sativa L.) varieties[END_REF][START_REF] Ohtsubo | Identification of domestic rice cultivars by RAPD method using milled rice grains as samples[END_REF] amplified fragment length polymorphisms [START_REF] Mackill | Level of polymorphism and genetic mapping of AFLP markers in rice[END_REF] and microsatellite analysis [START_REF] Bligh | Detection of adulteration of Basmati rice with non-premium long-grain rice[END_REF][START_REF] Vemireddy | Capillary electrophoresis is essential for microsatellite marker based detection and quantification of adulteration of Basmati rice (Oryza sativa)[END_REF][START_REF] Archak | High-throughput multiplex microsatelite marker assay for detection and quantitation of adulteration in basmati rice (Oryza sativa)[END_REF]. Of these techniques, microsatellite analysis appears to be the most successful and was recently used by the Food Standards Agency of the UK to survey the authenticity of Basmati rice on sale in the UK. The survey found that 17% of retail Basmati rice samples contained over 20% non-Basmati rice (Food Standards Agency, 2004). The adventitious mixing of Basmati with non-Basmati rice can occur during the production of Basmati rice and hence up to 7% non-Basmati rice may be present legally in "Basmati rice" ( agreed level of admixture in the UK Code of Practice). However the presence of more than 20% non-Basmati in some Basmati rice samples indicates wilful substitution, which if not declared would be illegal under food labelling rules. The accurate quantitation of the level of non-Basmati rice is therefore of paramount importance for successful prosecution. However, microsatellite analysis is a multi-step process, the accuracy of which is affected by, and not limited to, the selection of the rice varieties as appropriate calibrants, the microsatellites used for analysis, the methodology used for DNA extraction, PCR and capillary electrophoresis, the efficiency of the software used for data collection and the methodology used for subsequent data analysis. We have focused on improving the methodology used to calculate the level of adulteration with non-Basmati rice. We report a comparison of the current method (construction of a standard curve with a bestfit parabolic line) and possible alternative methods of constructing calibration curves for the measurement of non-Basmati rice in Basmati rice using microsatellite analysis, to enable a more accurate measurement. Calibration methods were compared using a range of measures of uncertainty. The calibration method that was found to give the most precise calibration was the linear regression of the 'ratio of Basmati peak area to non-Basmati peak area' against the 'ratio of the proportion of Basmati rice to the proportion of non-Basmati rice', which when used together with the measurement of uncertainty, should provide enhanced quantification of the level of adulteration of Basmati rice with non-Basmati rice.

Materials and methods

Sample DNA extraction and purification

Calibrants were prepared by gravimetrically mixing milled samples of Taraori (Basmati rice type) and Sherbati (long grain rice type). These samples were further ground to a fine powder, in a food processor, prior to DNA extraction using the Nucleon ® Phytopure kit (Amersham Pharmacia Biotech), with the following minor modifications: the cooled cell lysate was centrifuged at 4500g for 15mins prior to transferring 0.5ml supernatant to a fresh microcentrifuge tube and at the end of the procedure the DNA pellet was resuspended in TE buffer which had been previously heated to 85 o C.

PCR assay conditions

Each PCR reaction (25µL), contained 1x Amplitaq Gold ® reaction buffer, 0.625 Units AmpliTaq Gold ® DNA Polymerase (Applied Biosystems) and 0.5µM of each deoxynucleotide triphosphate (Sigma) and 5 pmols of sense (CTTAAATGGGCCACATGCG, 5' labelled with hexachlorofluorescein) and 5 pmols of anti-sense (TGCAAGAATCTGACCCGG) oligonucleotide primers (Sigma) for rice microsatellite marker RM222. DNA template was diluted 1:4 DNA:water and 5µL added per reaction. Reactions were assembled in Axygen thin walled PCR tubes and run on ABI 7900 PCR machine with the following thermal cycling protocol: 94 o C for 10 min followed by 45 cycles of 94 o C for 1 min, 55 o C for 1 min and 72 o C for 1 min with a hold for 60min at 60 o C.

Fluorescence gel electrophoresis

Amplicons were electrophoresed under denaturing conditions on an ABI377 (Applied Biosystems). Each reaction was run with a set of N,N,N',N'tetramethyl-6-carboxyrhodamine (TAMRA) labelled size standards (Applied Biosystems). The results were analysed using GeneScan analysis software (Applied Biosystems) and the total area, under each peak, for both alleles, at each calibration point, was calculated (Table 1).

Calibration methods

Four calibration methods were compared for their ability to estimate accurate measurements of non-Basmati in Basmati rice. The error uncertainty, standard error at the agreed limit of adulteration and 95% confidence intervals were determined. The methods of calibration investigated were as follows:

Power regression curve

A frequently used method of constructing calibration curves, where a power regression curve is fitted to the ratio of Basmati peak area to non-Basmati peak area against the proportion of non-Basmati rice, is shown in equation 1. Where r is the ratio of 'Basmati peak area' to 'non-Basmati peak area', p is the proportion of non-Basmati rice and a , b are constants estimated during model fitting.

Linear regression of the ratio of peak areas onto the ratio of proportions

An alternative option is to fit a linear regression to the ratio of Basmati peak area to non-Basmati peak area onto the ratio of the proportion of Basmati to the proportion of non-Basmati, as in equation 2.

Linear regression of the log of the ratio of peak areas onto the log of the ratio of proportions

This method fits a linear regression to the log (base10) of the ratio of Basmati peak area to non-Basmati peak area against the log of the ratio of the proportion of Basmati to the proportion of non-Basmati, as in equation 3.

f m e r + = ) ( log ) ( log 10 10 Equation 3
Where e and f are constants estimated during model fitting.

Hyperbolic Regression Curve

This alternative regresses the ratio of Basmati peak area to the non-Basmati peak area against the proportion of non-Basmati in the form of a hyperbolic line, as in equation 4. This is a generalized form of equation 2 that allows for the presence of an additional constant [START_REF] Bligh | Detection of adulteration of Basmati rice with non-premium long-grain rice[END_REF].

) 1 /( kp h g r + + = Equation 4
Where g , h and k are constants estimated during model fitting. associated with each calibration method was estimated by performing residual analyses (the residual is the difference between the observed response and its fitted model value) and by calculation of standard errors at the agreed limit of 7% non-Basmati rice in Basmati rice, by method of inverse calibration [START_REF] Brown | Measurement, regression and calibration[END_REF]. The residual analyses consisted of comparing the residual standard deviation and a graphical inspection to test modelling assumptions. In addition, 95% confidence intervals were calculated and the adjusted R 2 statistic (the proportion of total variability in the response that is accounted for by the model, adjusted for degrees of freedom) was recorded. Appropriate transformations were performed for equation 3 to enable an appropriate comparison of errors and confidence widths to the other calibration methods. Without the transformation, measures may falsely appear smaller, as they are on the log(ratio of peak areas) scale rather than the ratio of peak areas scale. All analyses were performed using GenStat ® 8.1 statistical software

Statistical methods

Statistical

Results and discussion

Microsatellite analysis has now become the 'gold standard' method for the identification and quantification of long grain adulterant rice in Basmati rice following the survey conducted by the Food Standards Agency of the UK in 2004 and the uptake of the methodology by analytical laboratories world wide [START_REF] Archak | High-throughput multiplex microsatelite marker assay for detection and quantitation of adulteration in basmati rice (Oryza sativa)[END_REF][START_REF] Vemireddy | Capillary electrophoresis is essential for microsatellite marker based detection and quantification of adulteration of Basmati rice (Oryza sativa)[END_REF]. Rice varieties are closely related and no one marker can definitively identify a variety of rice, therefore, a panel of microsatellite markers are used to build a profile of the rice varieties present.

Analysis of samples is usually a two step process, where the rice varieties of rice present is determined using up to 12 microsatellite markers, followed by quantitative analysis, using either a single or occasionally, two microsatellite markers, appropriate for the constituents of the sample. The choice of microsatellite markers for both the identification and quantification stages are a matter of choice, although some, for example RM1, RM55 and RM44 are used by many laboratories (Food Standards Agency, 2004;[START_REF] Archak | High-throughput multiplex microsatelite marker assay for detection and quantitation of adulteration in basmati rice (Oryza sativa)[END_REF]. The work presented in this study uses the microsatellite marker RM222 for illustrative purposes, since this marker easily distinguishes between the two rice varieties used to construct the calibration curve: Taraori basmati and Sherbati long grain. However, the approach outlined in this manuscript has also been shown to be applicable for quantitation using the microsatellite markers M16, RM44, RM171 and RM201 and should in fact be appropriate for any microsatellite marker optimised for quantification.

The data for the current study was generated by the analysis of multiple identical calibration curves, constructed from samples taken from single batches of Taraori Basmati and Sherbati long grain rice. In all 5 calibration curves were prepared and taken through the complete analysis, under repeatability conditions to provide independent, but linked datasets, enabling statistical analysis.

For illustration one of the five calibration data sets used to compare the calibration methods is shown in table 1. From this, the calculation of the ratio of peak areas and the ratio of proportions was determined. A visual check may lead the reader to believe that equation 3 (figure 3) has lesser scatter of points or tighter confidence intervals than the other equations.

However, the plots are on different scales (log(ratio of peak areas) for figure 3 compared to ratio of peak areas for figure 1, 2 and4) and so the spread can not be crudely compared in this way. An investigation of the maximum confidence interval widths for each calibration model (table 2), after appropriate transformations for equation 3, show equation 1 can have over 15 times the confidence width of equations 2 and 4. Equation 3 can have up to 4 times that of equations 2 and 4. Therefore equations 2 and 4 give more accurate estimation of the ratio of peak areas.

Graphical residual checks highlighted a non-random structure for equation 1 due to the poor fit of the model. Alternative model residuals were much improved with a random scatter of points around zero. This may be expected as the relationship between the ratio of peak areas against the ratio of proportions (equation 2) should be linear if the relative peak area for each type of rice is constant for each rice across the calibration range, or if relative peak areas are equal for each type of rice. In addition, the log of ratio of the peak areas against the log of ratio of proportions (equation 3) may be desirable as measurements based on PCR are cyclic in nature and therefore follow a lognormal distribution (assuming all other sources of error are minimal). Also, due to the reference concentration values often chosen, the log transformation can lead to a more evenly distributed set of calibration points. Adjusted R 2 values for each calibration data set for equations 2, 3 and 4 are mostly greater than 90%, where as the majority of adjusted R 2 values of equation 1 are under 90% (table 3). Hence equation 1 explains less of the variation in the data sets than the alternatives and so has a poorer fit.

Residual standard deviation values for each calibration data set for equations 2 and 4 are all less than 1.1 (table 4). Equations 1 and 3 can have over 5 and 2 times the residual standard deviation of equations 2 and 4 respectively. Thus equations 2 and 4 provide better fits to the calibration data.

Standard error values at the agreed limit of 7% non-Basmati rice in Basmati rice show equation 1 to be consistently larger than the alternatives (table 5).

Equation 2 has the smallest standard error for the first four calibrations and has the smallest maximum standard error overall. Hence, equation 2 performs more accurately when predicting at the limit of 7% non-Basmati rice.

An observation concerning the available data is the modest amount of information for the very low or very high percentage non-Basmati rice, where most assessments and predictions will be made. Therefore, it is advised that more reference materials at very high and very low concentrations are used for calibration.

In addition, when constructing calibration curves it is advised that the modelling checks that have been carried out during this investigation, such as graphical exploration of residuals, are continually performed. This enables monitoring of any underlying structure in the data which is not at first evident but which could lead to a poor fitting and so unreliable calibration curve being used for prediction of non-Basmati rice content.

Conclusion

In conclusion, after investigation into current methods for constructing calibration curves for quantitative microsatellite analysis, it is recommended that a linear regression of the ratio of Basmati peak area to non-Basmati peak area onto the ratio of the proportion of Basmati to the proportion of non-Basmati (equation 2) is used in future calibrations.

It was found that equations 2 and 4 gave more accurate assessments when comparing error uncertainty and structure, standard errors at the agreed limit of 7% non-Basmati rice and 95% confidence intervals, when compared with equations 1 and 3. Overall, for these data sets, equation 2 was found to give the most precise calibration, as it reported the lowest standard error at the agreed limit of 7% non-Basmati on average. For future data sets of this kind, equations 2 and 4 may give very similar performances. However, due to ease of implementation in a non-statistical package, equation 2 is favoured.

Using this calibration method, and the measurement uncertainty derived from it, will provide improved quantification of the level of adulteration of Basmati rice with non-Basmati rice. Furthermore, this method can be utilised for other measurements taken from an electropherogram where the aim is to compare peak areas.

  Where m is the ratio of the proportion of Basmati rice to the proportion of non-Basmati rice, i.e.

  analyses of five example calibration curves were performed by applying afore mentioned regression techniques to investigate which calibration method would provide the most accurate results for prediction. The uncertainty

  figures 1 to 4. The changes in uncertainty between models are demonstrated

Figure 2 Figure 3 Figure 4

 234 Figure 1 Calibration of data set 1 using equation 1 -fitted power regression of the ratio of peak areas* against the proportion of non-Basmati rice in the sample with 95% confidence intervals. * Ratio of peak areas = Basmati peak area / non-Basmati peak area

Table 1 .

 1 Total peak area under Basmati and Non-Basmati peaks for rice microsatellite marker RM222, from calibration data 1

	Percentage of Non-Basmati	Ratio of proportions #	Basmati peak area	Non-Basmati peak area	Ratio of peak areas*
	90	0.11	8573	107530	0.080
	90	0.11	5338	77420	0.069
	80	0.25	25523	117400	0.217
	80	0.25	16418	76782	0.214
	80	0.25	10755	49969	0.215
	60	0.67	45955	62983	0.730
	60	0.67	35775	48708	0.734
	60	0.67	36784	49601	0.742
	40	1.50	108668	71095	1.528
	40	1.50	44688	26491	1.687
	40	1.50	31717	18572	1.708
	30	2.33	45393	17985	2.524
	30	2.33	30896	11838	2.610
	30	2.33	79124	31434	2.517
	20	4.00	40269	5137	7.839
	20	4.00	35717	4785	7.464
	10	9.00	58007	5382	10.778
	10	9.00	37721	3891	9.694
	10	9.00	32834	3865	8.495
	7	13.29	48012	3125	15.364
	7	13.29	43202	2590	16.680
	7	13.29	43736	3061	14.288
	# Ratio of proportions = 'proportion of Basmati rice in sample' / 'proportion of
	non-Basmati rice in sample', e.g. 90% non-Basmati implies the ratio of
	proportions is 0.1/0.9=0.111
	* Ratio of peak areas = 'Basmati peak area' / 'Non-Basmati peak area'

Table 2 .

 2 Maximum width of confidence intervals on ratio of peak areas scale (after transformation for equation 3 to enable comparability)

	Calibration	Equation 1	Model Equation 2 Equation 3	Equation 4
	1	23.25	2.24	5.33	2.46
	2	37.28	4.51	7.20	4.72
	3	29.64	1.86	6.48	1.49
	4	42.99	3.76	11.26	4.48
	5	10.89	2.32	3.34	1.31

Table 3

 3 Adjusted R 2 values for calibration models

	Calibration	Equation 1	Model Equation 2 Equation 3	Equation 4
	1	89.1	95.8	98.6	95.9
	2	89.7	87.2	98.5	89.4
	3	86.6	96.7	98.3	98.3
	4	89.2	93.6	97.6	93.5
	5	91.0	91.5	97.7	98.2

Table 4 .

 4 Residual standard deviation for calibration models (after transformation for equation 3 to enable comparability)

	Calibration	Equation 1	Model Equation 2 Equation 3	Equation 4
	1	3.529	1.018	1.468	1.052
	2	6.033	1.080	2.457	1.068
	3	4.629	1.048	1.839	1.029
	4	6.106	1.022	2.297	1.048
	5	1.113	1.054	1.291	1.043

Table 5 .

 5 Standard error of the calibration models at the agreed limit of 7% non-Basmati rice in Basmati rice (after transformation for equation 3 to enable comparability)

	Calibration	Equation 1	Model Equation 2 Equation 3	Equation 4
	1	0.0090	0.0023	0.0043	0.0032
	2	0.0088	0.0043	0.0046	0.0077
	3	0.0098	0.0020	0.0047	0.0025
	4	0.0095	0.0030	0.0064	0.0046
	5	0.0078	0.0032	0.0055	0.0006
	Maximum	0.0098	0.0043	0.0064	0.0077

http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.ukFood Additives and Contaminants


K A Ehlert
email: karl.ehlert@tno.nl

C W E Beumer

M C E Groot

bisphenol A into water from polycarbonate baby bottles during microwave heating

Keywords: migration, residual content, bisphenol A (BPA), polycarbonate baby bottles, microwave

Migration study of bisphenol A into water from polycarbonate baby bottles during microwave heating

Introduction

Migration of bisphenol A from polycarbonate materials under different testing conditions applying traditional heating is well described in literature. Brede et. al. (2003) and Boots (2004) examined the migration of bisphenol A from polycarbonate baby bottles after dishwashing, boiling and brushing, Tan et al. (2003) and [START_REF] Biles | Determination of bisphenol-A in reusable polycarbonate foodcontact plastics and migration to food-simulating liquids[END_REF] investigated the leaching of bisphenol A form old and new baby bottles. Yoshida et. al. (2003) andMaragou et. al. (2007) determined the migration of bisphenol A after repeated use.

Whereas the influence of time, pH, and temperature on the migration behaviour of bisphenol A from polycarbonate is well investigated, only a few studies have examined the effects of electromagnetic radiation in microwave heating. The results of these studies by Mountfort et. al. (1997) andKawamura et. al. (1998) indicate that migration behaviour is not influenced by electromagnetic radiation on the plastic under chosen testing conditions. The recent opinion of the European Food Safety Authority on bisphenol A (EFSA, 2006) indicated that not much information is available on the migration behaviour of bisphenol A form polycarbonate during consecutive microwave heating.

The aim of this study was to establish more information regarding migration behaviour of bisphenol A into water during microwaving of polycarbonate baby bottles. More data in the public domain will be helpful to support the safety of polycarbonate plastic. Published migration studies using conventional heating were mostly performed with water as the food simulant. To allow comparison of data from microwave heating with data of conventional heating, water was used in this study. The selection of water is in accordance with Council Directive 85/572/EEC specifying water as the simulant to be used for milk, although the For the purpose of the study polycarbonate baby bottles from different brands sold in Europe were collected and the initial residual content as well as the migration of bisphenol A after repeated microwave heating were determined. The overall procedure was chosen to represent typical conditions for a microwave heating procedure as derived from recommendation from the baby bottles manufacturers. Eighteen types of bottles from different brands sold in Europe were collected: ten major brands sold across Europe, 3 local brands from UK, 3 local brands from the Netherlands and 2 local brands from Germany. To warrant consistent quality all bottles of each brand were purchased from a single source.

Materials and Methods

F

Experimental

Sample characterisation

One bottle of each brand was examined by means of infrared analysis to confirm that the bottles are made of polycarbonate. A piece was cut and was examined on both sides using a Perkin Elmer Spectrum GX FT-IR System. Spectra were recorded in the ATR mode (Golden Gate) from 580 cm -1 -4000 cm -1 . Spectra were searched against commercial libraries to identify the polymer.

Residual content of bisphenol A

A sample of each brand was weighed and cut into pieces of about 2x2 cm. All pieces (the whole bottle was used) were placed in an Erlenmeyer flask. For each g of polycarbonate material 10 ml of dichloromethane was added. Bisphenol F (Aldrich) was added to the dichloromethane as internal standard at a concentration of 0.8 mg.l -1 . The solution was refluxed until the polycarbonate was completely dissolved. A volume of methanol (0.5 x volume of dichloromethane) was slowly added to precipitate the polymer fraction, while continuing refluxing for about 2 min. The solution was filtered, and the filtrate was stored in a refrigerator for at least 6 hours. An aliquot of the clear liquid containing the residual bisphenol A was transferred into a vial and analysed by HPLC. This whole procedure was performed in duplicate.

Instrumental conditions

HPLC analysis was performed using a Alliance 2695 HPLC (Waters) equipped with an automatic sampler/injector and a Fluorescence 474 detector (Waters) and a PDA 996 (UV) detector (Waters). The column was a Sunfire TM C18 3.5 µm 3.0x150 mm column (Waters), kept at 35°C. Elution was performed using a gradient as shown in table 1. Fluorescence detection was performed at an excitation wavelength set at 278 nm and emission wavelength set at 305 nm. UV spectra were recorded for identification purposes.

Recovery

One sample was dissolved in dichloromethane as described above. The dichloromethane was divided in aliquots of 30 ml which were spiked at a level of 0.3 mg.l -1 . The recovery in a spiked sample extract was 103.3%. The working detection limit (WDL calculated from calibration curve according to DIN 32645) was 0.5 mg/kg.

Migration of bisphenol A Sterilisation conditions

Sterilisation conditions were derived from recommendation from the baby bottles manufacturers. For each brand 6 specimens were immersed in boiling water (water purified using a Milli-Q gradient A10 System) for 5 min. After this, the bottles were placed on a grid and left to dry for at least 3 hours.

Heating and cooling conditions

The microwave oven (Whirlpool Jet Stream JT357) was operated at maximum power (jetmode, nominal power 1000 W). The power output of the microwave oven was determined as described in EN 14255:2002. This was carried out once before the migration studies, once in the middle of the series and once after finishing the migration tests. The average power output of the microwave oven was 728 W (RSD 3%). For one sample a temperature profile was recorded during microwave heating using a calibrated fibre-optic thermometer ( 950Multichannel Fluoroptic Thermometer (Luxtron)). One probe was placed in the centre of the bottle and one probe was placed at the inside wall of the bottle. The bottle was filled with 100 ml of water and heated in the microwave oven without subsequent cooling down in the water bath. The microwaving was started after 5 sec, boiling was achieved after 1 min and 54 sec and maintained one minute till 2 min and 54 sec, after which the microwave door was opened. Figure 1 shows the temperature profiles. The temperature profiles indicate no difference between the temperature at the centre of the bottle and the temperature at the wall.

Figure 1. Temperature profile

To determine the loss of water during microwaving, the weight of a bottle filled with 103 g of water was determined before and after microwave heating. The difference in weight was 9.5 g, which means that 9 % of water was evaporated during microwave treatment. To analyse how long it takes that the microwave heated bottle content cools down to a temperature of 37°C in a water bath at 20°C, a bottle of was filled with 100 ml of water and a conventional thermometer was inserted at the centre of the bottle. After heating to 100°C, a temperature of 37°C in a water bath at 20°C was reached after 7 min and 44 sec.

Sample processing

After sterilisation, the dry bottles were filled with 100 ml of water (Sigma Aldrich, HPLCgrade) at room temperature, and placed in the centre of the microwave oven. Bottles with a volume greater than 200 ml were filled with 200 ml of water. The water in the bottle was heated until boiling, and boiling was maintained for 1 minute with unchanged power capacity.

After this period the bottle was placed in a water bath at 20°C until the water in middle of the bottle had reached a temperature of 37°C. Then the content of the bottle was transferred into glassware to be analysed. The emptied bottle was rinsed 3 times by shaking with 50 ml water (purified using a Milli-Q gradient A10 System) at room temperature, for 15 seconds; the water was discarded after rinsing. The bottle was placed on a grid and left to dry for at least 3 hours. This rinsing and drying procedure was chosen to simulate normal use of the bottle. The procedure as described above was repeated another two times on the same bottle. Thus, 3 migration extracts were prepared for each test specimen.

Analytical method

Migration extracts were fortified with deuterated (d 16 -) bisphenol A (Aldrich) as internal standard at a concentration of 40 ng per 100 ml extract. The samples were extracted and concentrated using SPE (Solid Phase Extraction) columns (ENV+, 100 mg). The SPE columns were placed on a SPE station, and solvated with 3 ml acetone, followed by 3 ml methanol, and conditioned with 3 ml of water. The water extracts were transferred through the SPE columns by applying a vacuum. Before elution, the SPE packing was dried by applying a vacuum for about 20 min. The SPE columns were eluted with 2 ml acetone. The acetone was evaporated and the residue was re-dissolved in 10 µl pyridine and 90 µl MSTFA (N-Methyl-N-(trimethylsilyl) trifluoroacetamide) in a GC-vial, and heated for 45 minutes at 40°C.

Instrumental conditions

GC-MS analyses were achieved using an Agilent 6890N GC coupled to a Agilent 5973N mass spectrometer. Gas Chromatographic conditions: column HP-5MS, 0.25mm x 30m 0.25µm film thickness (Agilent); constant flow helium 1.5 ml.min Bisphenol A and the internal standard deuterated bisphenol A were quantified using extracted ion chromatograms at m/z 357 and m/z 368 respectively.

Calibration

Calibration solutions were prepared by spiking 100 ml water (Sigma Aldrich, HPLC-grade) samples with bisphenol A (Aldrich) at a level of 0.05, 0.1, 0.2, 0.5, 1, 2 and 5 µg.l -1 .

Quantification was performed using calculation from regression parameters according to DIN 32645. The working detection limit (WDL calculated from calibration curve according DIN 32645) was 0.1 µg.l -1 .

Repeatability and recovery

The repeatability and recovery of the method was determined by spiking 5 aliquots of water (Sigma Aldrich, HPLC-grade) at a level of 1 µg.l -1 . The mean recovery of 5 spiked samples was 95%. The standard deviation was 2 %.

Recovery in migration extracts

Twelve specimens of one sample were sterilised and migration extracts were obtained. The contents of the 12 specimens were combined and divided in aliquots of 90 ml. Three aliquots were spiked at a level of 0.1 µg.l -1 and 3 aliquots were spiked at a level of 0.2 µg.l -1 . The recovery of spiked migration extracts was 113.7% for the extracts spiked at 0.1 µg.l -1 and 91.4% for the extracts spiked at 0.2 µg.l -1 . The concentration of the non-spiked extracts was 0.11 µg.l -1 .

Results and discussion

The FT-IR analysis confirmed that all 18 samples were made of polycarbonate. Figure 2 shows a typical FT-IR spectrum of a polycarbonate baby bottle. Characteristic wavelengths are 1768 cm -1 , 1503 cm -1 , 1244 cm -1 and 3040 cm -1

Figure 2. FT-IR spectrum of a polycarbonate baby bottle Residual content of bisphenol A

Table 2 shows the results of the residual content of bisphenol A in the polycarbonate baby bottles. This shows that the residual content of bisphenol A in polycarbonate baby bottles is in range of 1.4 to 35.3 mg.kg -1 . Figure 3

Migration of bisphenol A

Table 3 gives the average results of the migration of bisphenol A from the polycarbonate baby bottles into water after 3 microwave heating cycles, indicating that the migration of bisphenol A from the polycarbonate baby bottles into water ranged from < 0.1 to 0.7 µg.l -1 .

Figure 5 -7 present GC-MS chromatograms for the determination of migration of bisphenol A into water after microwave heating.

Table 3. Average results of the migration of bisphenol A into water after 3 microwave heating cycles.

Statistical analysis

To determine if there is a correlation between the amount of the residual content of bisphenol A in the bottles and the migration of bisphenol A, Spearman's correlation coefficients were calculated. This coefficient is a non-parametric version of Pearson's correlation coefficient, in which the actual data is converted to rankings before calculating the coefficient. The Spearman's correlation coefficients reveal that there is no correlation between the residual content and the migration of bisphenol A. Furthermore it was tested whether the residual content of bisphenol A differs between migration extracts. This was done using the Kruskal-Wallis test, which is a one-way analysis of variance by ranks. The p-value for this test was 0.3690, so there was no difference in bisphenol A between migration extracts.

Conclusions

The residual content of bisphenol A in the polycarbonate baby bottles ranged from 1.4 to 35.3 mg.kg -1 . Migration of bisphenol A into water was found to be in the range of < 0.1 to 0.7 µg.l -1 . The data presented shows that during 3 microwave heating cycles of a baby bottle made from polycarbonate, no effects of electromagnetic radiation on the migration of bisphenol A into water from polycarbonate was observed.Statistical analysis (Spearman correlations) showed there is no correlation between the amount of the residual content of bisphenol A in the bottles and the migration of bisphenol A. Furthermore, there was no statistical difference (Kruskal-Wallis correlation) in the amount of bisphenol A in the consecutive migration extracts. All levels found were well below the specific migration limit of 0.6 mg/kg specified for bisphenol A (

  and 4 present an HPLC chromatogram for the determination of the residual content of bisphenol A in the polycarbonate.

Figure 3 .

 3 Figure 3. HPLC chromatogram of a sample Rt bisphenol A 15.2 min

Figure 5 .

 5 Figure 5. GC-MS chromatogram of a standard bisphenol A at a level of 1 µg.l-1.

Figure 6 .

 6 Figure 6. GC-MS chromatogram of a sample

Spearman

  p-value is given between brackets) Residual content versus 1 st migration extract: r=0.005 (p=0.9833) Residual content versus 2 nd migration extract: r=0.055 (p=0.8271) Residual content versus 3 rd migration extract: r=-0.104 (p=0.6803)

Table 2 .

 2 Results of the residual content of bisphenol A in polycarbonate baby bottles.

  Commission Directive 2004/19/EC) 14.00 15.00 16.00 17.00 18.00 19.00 20.00 21.00 22.00 23.00 24.00 25.00

	Page 13 of 19	Food Additives and Contaminants Food Additives and Contaminants Food Additives and Contaminants	Page 10 of 19 Page 16 of 19
	F o r P e dishwashing, boiling and brushing, Food Additives and Contaminants 20, 2003, 684-689 Time (min) Flow %A * %B * %C * Sample Residual content (mg.kg -1 ) 96.9 360.00 360.00 Migration (µg.l -1 ) 90 320.00 340.00 320.00 340.00 15.222 Sample (ml.min -1 ) Number A B Average number First cycle Second cycle Third cycle 75 80 85 260.00 280.00 300.00 13.836 260.00 280.00 300.00 13.860 Commission Directive 2004/19/EC of 1 March 2004 amending Directive 2002/72/EC relating 0 0.4 0 95 5 1 2,6 1,1 1 0.10 <0.10 <0.10 70 220.00 240.00 220.00 240.00 1,9 65 200.00 200.00 to plastic materials and articles intended to come into contact with foodstuffs. Official 2 0.4 0 95 5 20 0.4 0 0 100 2 1,8 2,8 2,3 3 2,9 3,2 3,1 2 0.12 0.11 60 EU 180.00 EU 180.00 0.14 3 0.22 0.16 50 55 %T 140.00 160.00 160.00 15.192 140.00 0.30 40 45 100.00 120.00 100.00 120.00 Journal of the European Communities, L71, 8-21 Commission Directive 2007/19/EC of 30 March 2007 amending Directive 2002/72/EC relating to plastic materials and articles intended to come into contact with food and Council Directive 85/572/EEC laying down the list of simulants to be used for testing migration of constituents of plastic materials materials and articles intended to come into contact with foodstuffs. Official Journal of the European Communities, L91, 17-36 Council Directive 85/572/EEC of 19 December 1985 laying down the list of simulants to be F o r 25 0.4 80 0 20 35 0.4 80 0 20 37 0.4 0 0 100 38 0.4 0 95 5 45 0.4 0 95 5 F o r 4 3,5 4,5 4 0.26 0.17 0.13 120 35 60.00 80.00 60.00 80.00 4,0 5 6 2,4 2,5 2,5 6 27,2 30,0 5 0.13 0.11 25 30 20.00 40.00 13.600 20.00 40.00 13.625 0.18 6 <0.10 <0.10 20 0.00 10.00 11.00 12.00 13.00 14.00 15.00 16.00 17.00 18.00 19.00 20.00 0.00 10.00 11.00 12.00 13.00 14.00 15.00 16.00 17.00 18.00 19.00 20.00 100 15 Minutes Minutes <0.10 10 28,6 7 4,6 6,7 5,7 8 7,2 4,0 5,6 9 23,4 26,5 25,0 10 4,1 5,9 5,0 11 4,7 3,8 4,3 12 33,8 36,7 35,3 13 14,4 14,3 14,4 F o r 7 0.10 0.10 0.1014 0.10 8 <0.10 0.11 <0.10 9 <0.10 <0.10 <0.10 10 0.19 0.12 0.11 11 0.13 <0.10 <0.10 12 0.49 0.73 F o 20 40 60 80 Inside wall 4000.0 3600 3200 2800 2400 2000 1800 1600 1400 1200 1000 800 580.0 3.9 cm-1 Temperature (C) Centre F o F o F o F o 0.28 13 0.13 <0.10 <0.10 r 0 r r r r used for testing migration of constituents of plastic materials and articles intended to come into contact with foodstuffs. Official Journal of the European Communities, L372, 14-21 European Food Safety Authority, Opinion of the Scientific Panel on food additives, flavourings, processing aids and materials in contact with food (AFC) related to 2,2-bis(4-hydroxyphenyl)propane. Question number EFSA-Q-2005-100. The EFSA Journal 428, P e e r P e e r 14 3,4 4,2 3,8 15 1,4 1,4 1,4 16 2,5 2,7 2,6 17 2,5 3,1 2,8 18 25,6 16,9 21,3 P e e r 14 0.17 <0.10 0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 0.10 15 0.32 0.11 0.11 16 0.10 <0.10 P Time (min) P P P P <0.10 17 <0.10 0.12 <0.10 18 0.21 0.26 0.14 e e r e e r e e r e e r e e r e r R e v i e 2006, 1-75 Kawamura, Y., Koyano, Y., Takeda, Y., Yamada, T., Migration of bisphenol A from polycarbonate products, Journal of the Food Hygienic Society of Japan 99, 1998, 206-212 Maragou, N. C., Makri, A., Lampi, E. N. Thomaidis, N. S., Koupparis, M. A, Migration of bisphenol A from polycarbonate baby bottles under real use conditions, Food Additives and Contaminants, 2007, DOI 10.1080/02652030701509998 R e v i e w R e v i e w R e v i e w R e v i e w R e v i e w R e v i e w R e v i e w R e v i e w w Mountfort, K. A., Kelly, J., Jickells, S. M., Castle, L., Investigations into the potential degradation of polycarbonate baby bottles during sterilization with consequent release of bisphenol A, Food Additives and Contaminants 14, 1997, 737-740 O n O n O n O n O n O n O n O n O n l Tan, B., Mustafa, A., Leaching of bisphenol A from new and old babies' bottles and new babies' teats, Asia Pac. Public Health 15, 2003, 118-123 l y l y l y l y l y l y l y l y
	Yoshida, H., Harada, H., Nohta, H., Yamaguchi, M., Liquid chromatographic determination y of bisphenols based on intramolecular excimer-forming fluorescence derivatization,
		Analytica Chemica Acta 488, 2003, 211-221

http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk

http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.ukFood Additives and Contaminants

Acknowledgement

The authors thank PlasticsEurope, the European Association of Plastics Manufacturers for their sponsorship, scientific and technical contribution. The authors would also like to thank S. Bijlsma and C.M. Rubingh (TNO) for the statistical contribution and E.K Zondervan-van den Beuken and W.D. van Dongen (TNO) who carefully reviewed the last version of the paper.


Malcolm Driffield

Nick Harmer

Emma Bradley

Alwyn R Fernandes

Martin Rose

David Mortimer

Pamela Dicks

la diffusion de documents scientifiques de niveau

Keywords:

recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

The determination of brominated flame retardants in food by liquid chromatography with tandem mass spectrometric detection: diastereoisomer specific hexabromocyclododecane and tetrabromobisphenol A Introduction Hexabromocyclododecane (HBCD) and tetrabromobisphenol A (TBBPA), see Figure 1, are brominated flame retardants (BFRs) that are used to inhibit the ignition of combustible materials and are also effective at hindering the spread of fire (D' Silva et al. 2004). They are used in the manufacture of a wide range of materials including rubbers, plastics and textiles, which are in turn used to make many different commercially available products ranging from foams and textiles in furniture and vehicles, to components in electronic devices.

HBCD is an additive BFR and can be incorporated into a material before, during or after polymerisation. TBBPA is a reactive BFR and forms chemical bonds with the material into which it is incorporated. Any unreacted or incompletely incorporated molecules have the potential to diffuse into the environment. This is of concern due to the toxic, persistent and bioaccumulative properties of the compounds and their largescale use. HBCD and TBBPA and have been detected in environmental samples such as water, air, sediment and biota [START_REF] Darnerud | Toxic effects of brominated flame retardants in man and in wildlife[END_REF][START_REF] Hakk | Metabolism in the toxicokinetics and fate of brominated flame retardants -a review[END_REF], D'Silva et al. 2004[START_REF] Tollback | Determination of the flame retardant tetrabromobisphenol A in air samples by liquid chromatography-mass spectrometry[END_REF].

It is generally accepted that the major part of human exposure to brominated pollutants such as BFRs is likely to be through the diet, as has been shown for other halogenated compounds such as chlorinated dioxins and polychlorinated biphenyls (Schecter et 'Silva et al. 2004[START_REF] Fernandes | Brominated and chlorinated dioxins and brominated flame retardants in Scottish shellfish: Methodology, occurrence and human dietary exposure[END_REF]). However, there is relatively little data published on the levels of HBCD and TBBPA in food and where data is available it is often not diastereoisomer specific for HBCD. It is desirable from a toxicological point of view to determine the concentration of each diastereoisomer separately as these may have different biological activities. It is because of this and the potential to diffuse into the environment that these compounds have become the focus of recent studies. A study into the dietary intake of BFRs by the Dutch population was carried out in 2003 with concentrations in most of the samples below the 0.02 µg/kg limit of detection (LOD) [START_REF] Sorkina | Dietary intake of brominated flame retardants by the Dutch population[END_REF]. For the samples where BFRs were detected, levels of total HBCD were reported up to 12 µg/kg for Ijsselmeer eel and up to 3.4 µg/kg for hatched eel for TBBPA. A Swedish study of biota for contaminants reported a fat weight concentration range of 4.0 -18 µg/kg total HBCD for herring landed along the Swedish Baltic coast [START_REF] Asplund | Comparison of spatial and temporal trends of methyoxylated PBDEs, PBDEs, and hexabromocyclododecane in herring along the Swedish coast[END_REF]). In the UK elevated concentrations of HBCD were detected in fish from the river Skerne, but these were caught in the vicinity of a BFR manufacturing site and were unlikely to be representative of the general levels of HBCD in fish in the UK (Food Standards Agency a). However, the data demonstrates the bioavailability and uptake potential of these contaminants.

In much of the occurrence data, HBCD is reported as total HBCD. This is because HBCD is susceptible to degradation, interconversion and adsorption during analysis using elevated temperatures such as gas chromatography (GC). Studies show that the HBCD diastereoisomers are thermally labile and interconvert at temperatures greater than 160 o C [START_REF] Remberger | The environmental occurance of HBCD in Sweden[END_REF]). Even at temperatures below 160 o C the diastereoisomers were not separated chromatographically due to peak broadening and only total HBCD concentrations were reported (the sum of α, β and γHBCD [START_REF] Hale | Polybrominated diphenyl ether flame retardants in the North American environment[END_REF]. Liquid chromatography (LC) has become popular for the separation of the diastereoisomers as it avoids the high temperatures of the GC methodologies. The selectivity and sensitivity afforded by tandem mass spectrometric (MS/MS) detection enables rapid analysis of many different sample types, determining very low concentrations of analytes [START_REF] Dodder | Analysis of hexabromocyclododecane diastereomers and enantiomers by liquid chromatography/tandem mass spectrometry: Chromatographic selectivity and ionization matrix effects[END_REF], RJ Law et al. 2006[START_REF] Suzuki | Determination of hexabromocyclododecane diastereoisomers and tetrabromobisphenol A in water and sediment by liquid chromatography/mass spectrometry[END_REF]. The UK Food Standards Agency (FSA) commissioned a study of farmed and wild fish, shellfish and fish oil dietary supplements for brominated chemicals including HBCD and TBBPA using LC-MS/MS (Food Standards Agency b). TBBPA was not detected in any of the 48 fish samples nor the 10 fish oil dietary supplement samples above the LOD (0.03 -0.05 µg/kg whole weight). The predominant HBCD diastereoisomer detected was the α diastereoisomer and the concentrations were in the ranges 0.07 -5.1 µg/kg, 0.03 -0.44 µg/kg and 0.03 -0.22 µg/kg for α, β and γHBCD respectively in the fish samples and 0.42 -5.0 µg/kg, 0.19 -0.41 µg/kg and 0.20 -0.44 µg/kg for α, β and γHBCD respectively in the fish oil samples. This paper describes the methodology and results of two studies into the levels of TBBPA and HBCD (α, β and γ diastereoisomers) in UK food: total diet study (TDS) samples from 2004, including bread, miscellaneous cereals, carcass meat, offal, meat products, poultry, fish, oils and fats, eggs, sugars and preserves, green vegetables, potatoes, other vegetables, canned vegetables, fresh fruit, fruit products, milk, dairy products and nuts, and shellfish from Scottish inshore and offshore harvesting areas.

Materials and methods

F

Chemicals

Solutions (50 µg/mL) of the α, β and γ diastereoisomers of 1,2,5,6,9,10hexabromocyclododecane and 3,3',5,5'-tetrabromobisphenol A, and their 13 C analogues were purchased from Greyhound Chromatography and Allied Chemicals (Merseyside, UK). Methanol, hexane, dichloromethane, tetrahydrofuran, water (all HPLC fluorescence grade), anhydrous sodium sulfate (laboratory reagent grade) and concentrated sulphuric acid (analytical reagent grade) were obtained from Fisher Chemicals (Loughborough, UK). Activated silica (YMC gel) was purchased from YMC-Europe (Weselerwald, Germany). Sulfuric acid modified silica gel (40:60 w/w) was prepared in-house by adding sulfuric acid (1000 g) to activated silica (1500 g) and agitating on a roller mixer until a free-flowing powder was formed (approximately 6 h).

Samples Total diet study

Samples were collected as a part of the UK 2004 total diet study [START_REF] Peattie | Reorganization of the British total diet study for monitoring food constituents from 1981[END_REF]).

These were collected throughout the UK at fortnightly intervals and on each date a different location was chosen to reflect the UK population density. The food was prepared for consumption and combined, with the exception of beverages (Group 17), to give nineteen food groups representing the UK diet for 2004. The groups are listed in Table I. The pooled samples for the fruit, vegetable and milk based groups were freezedried due to the high water content and the resulting powders were thoroughly mixed before taking sub-samples for analysis. All other samples were analysed as received.

Samples were stored at -20 o C and re-homogenised prior to analysis.

Shellfish

Individual sub-samples of mussels, oysters and scallops were collected between January and March 2006. This period was selected to capture the pre-spawning period and coincides with the time when fat levels are highest. The samples were representatively pooled and homogenised to yield thirty-five composite analytical samples. As scallops are sometimes retailed as just adductor muscles, these samples were divided into separate adductor and gonad portions prior to pooling. Details of the sampling plan are reported elsewhere (Food Standards Agency c). Samples were stored at -20 o C and rehomogenised prior to analysis. Further details have been published elsewhere [START_REF] Fernandes | Brominated and chlorinated dioxins and brominated flame retardants in Scottish shellfish: Methodology, occurrence and human dietary exposure[END_REF]).

In-house reference material

An in-house reference material (IHRM) was prepared by adding α, β and γHBCD and TBPPA (2.5 µg of each dissolved in 1 mL tetrahydrofuran) to sunflower oil (500 g) to give a nominal concentration of 5 µg/kg. This was stirred well and stored at room temperature in the absence of light.

Extraction and clean-up procedure

In each study samples were analysed in batches. Each batch consisted of: five samples, each in duplicate; over-spiked samples in duplicate; duplicate IHRM; over-spiked IHRM; a procedural blank sample of sunflower oil (that used to prepare the IHRM, previously shown to contain no HBCD or TBBPA). Four portions of each sample were taken (20 g):

• Portions 1 and 2 were spiked with internal standards (5 ng each of 13 C αHBCD, 13 C βHBCD, 13 C γHBCD and 13 C TBBPA) and the four analytes (25 ng each of αHBCD, βHBCD, γHBCD and TBBPA), to allow recovery corrected concentrations to be determined.

• Portions 3 and 4 were spiked with only internal standard (5 ng each of 13 C αHBCD, 13 C βHBCD, 13 C γHBCD and 13 C TBBPA). Two procedural blanks were prepared and analysed in each batch by spiking anhydrous sodium sulphate (100 g) with internal standards (5 ng each of 13 C αHBCD, 13 C βHBCD, 13 C γHBCD and 13 C TBBPA). The IHRM was analysed in duplicate (5 g) in each batch along with a blank sample (5 g) of the sunflower oil (spiked with 5 ng each of 13 C αHBCD, 13 C βHBCD, 13 C γHBCD and 13 C TBBPA) and a sample of the sunflower oil (5 g) spiked at the time of extraction (5 ng each of 13 C αHBCD, 13 C βHBCD, 13 C γHBCD and 13 C TBBPA and 25 ng each of αHBCD, βHBCD, γHBCD and TBBPA).

The samples were left to allow the internal standards and spiked analytes to infuse for 30 min prior to extraction. Each sample was mixed with anhydrous sodium sulphate (100 g) and hexane:dichloromethane, 60:40 (v/v) (250 mL) was added. The mixture was homogenised using an Ultra Turrax for 1 min, left to stand for a further 15 min and sulphuric acid modified silica gel (100 g) was added. The slurry was homogenised for 5 min, filtered and the filtrate collected. The silica residue was washed with hexane:dichloromethane, 60:40 (v/v) (50 mL) and the washings were combined with the original filtrate. The filtrate and washings were transferred to a round bottom flask and reduced in volume to approximately 10 mL using a rotary evaporator. This was then quantitatively transferred to a glass vial and evaporated to dryness under nitrogen.

Methanol (120 µL) was added, the vial capped, vortex mixed for 20 seconds, ultrasonicated for 5 min, vortex mixed for another 20 seconds and the solution transferred to a LC-MS/MS glass vial. Water (30 µL) was added and the vial was capped and vortex mixed for 20 seconds. Solvent standards were prepared in the range 5 -600 ng/mL for the four analytes and analysis was carried out using LC-MS/MS in multiple reaction monitoring mode (MRM).

LC-MS/MS analysis

A Waters (Hertsford, UK) Alliance 2695 LC system was used. The LC column was a Waters Sunfire column (C 18 ), 150 mm long, 2.1 mm internal diameter, 3.5 µm diameter silica particles, maintained at 30 o C in a thermostated column oven. The mobile phase consisted of methanol and water with a flow rate of 0.2 mL/min. A gradient was used starting at 80% methanol and changing to 100 % methanol over 20 min. An injection volume of 40 µL was used. The MS/MS system was a Micromass (Manchester, UK) Quattro Ultima triple quadrupole MS used in negative electrospray ionisation mode.

The capillary voltage was 3 kV with a source temperature of 130 o C. Desolvation gas was nitrogen at 700 L/h and the desolvation temperature was 300 o C. Collision-induced dissociation was performed using argon. MRM was used for quantification and confirmation. The channels monitored for the three HBCD diastereoisomers were 640.3>78.9 (quantification) and 640.3>81.1 (confirmation) and the internal standard channel was 652.3>78.9. These channels used a collision energy of 17 eV and a cone voltage of 35 V. The TBBPA channels were 542.9>447.7 for quantification and 542.9>419.9 for confirmation with a cone voltage of 35 V and collision energy of 17 eV. For the internal standard the 554.5>430.7 channel was monitored with a cone voltage of 50 V and collision energy of 44 eV.

Results and discussion

Method performance

In both studies quality control and quality assurance measures were taken. Linearity of the solvent standards over the concentration range 5 -600 ng/mL was rectilinear with correlation coefficients of 0.995 or greater and residual values of +/-20% or less. All samples were over spiked with each analyte to allow recovery corrected concentrations studies and this provides evidence that the method is robust enough to accommodate a wide range of food types. As there are no certified reference materials available for these analytes, an IHRM was run with every batch of samples. Sunflower oil was used to prepare the IHRM as the high lipid content makes this a challenging matrix to extract and purify. The oil was tested and shown to contain no HBCD or TBBPA so was spiked to give a concentration of 5 µg/kg. The average concentrations for this IHRM determined during the TDS samples were 5.1 µg/kg, 5.2 µg/kg, 4.9 µg/kg and 4.8 µg/kg for α, β and γHBCD and TBBPA respectively with relative standard deviation (RSD) values of 6.2%, 9.0%, 4.7% and 4.4% (n=10). For the shellfish average concentrations of 5.0 µg/kg, 4.9 µg/kg, 5.1 µg/kg and 5.0 µg/kg were determined with RSD values of 3.1%, 2.8%, 4.8% and 3.9% (n=14) for α, β and γHBCD and TBBPA respectively.

LODs were calculated as the average concentration plus two times the standard deviation of the concentration of any analyte detected in the procedural blank samples.

LOD values are given as less than (<) values in Tables I -IV when no HBCD or TBBPA were detected. These are sample specific as different masses of sample were taken depending upon the total amount of sample received. An estimation of the measurement uncertainty was calculated using the replicate samples and over-spiked samples. An average of the duplicate values was calculated and then the two individual values were normalised to the average to give a percentage value. This was then averaged out over the whole data set to give values in the range 30% -40% for the TDS study and 15% -40% for the shellfish study.

Total Diet Study for 2004

The UK Total Diet Study (TDS) is used to provide information on the dietary exposure of the general population, and different sub-groups of the population, to nutrients and [START_REF] Peattie | Reorganization of the British total diet study for monitoring food constituents from 1981[END_REF]. These studies are an essential aid to verifying that exposure to these contaminants does not give cause for health concerns.

Specified retail food samples are purchased at fortnightly intervals from different locations in the UK and are prepared for consumption and combined to produce twenty food groups representing their relevant importance in the UK diet. Table I lists the individual groups (with the exception of group 17, beverages, which was not included in this study). Analysis of one year's combined samples ensures that a large, diverse base of individual samples sourced from across the UK are included, and the composite samples represent average national dietary habits.

Table I gives the whole weight concentration of the three HBCD diastereoisomers and TBBPA detected in each TDS sample. In all cases, TBBPA was not detected above the LOD, which is also given in Table I. Overall the HBCD concentrations were low, all concentrations detected ranged from 0.02 to 0.3 µg/kg. In nine groups (meat, fish, vegetable and nut containing groups) αHBCD was the predominant diastereoisomer.

The meat and fish containing groups saw HBCD profiles with αHBCD predominating as opposed to the γ diastereoisomer that dominates in the technical and commercial standards available (Winer Sorkina et al, 2003, Food Standards Agency b, Fernandes et al. 2005). It has been reported that the αHBCD predominance is a result of selective metabolism or a biotransformation process [START_REF] Zegers | Levels of hexabromocyclododecane in harbor porpoises and common dolphins from western European seas, with evidence for stereoisomer-specific biotransformation by cytochrome P450[END_REF]

, K Law et al. 2006).

There were nine groups where no HBCD diastereoisomers were detected above the LOD. In the remaining case, fresh fruit, the αHBCD and βHBCD concentrations were the same (0.3 µg/kg). II. The UK independent Committee on Toxicity of Chemicals in Food, Consumer Products and the Environment (COT) has previously concluded that Tolerable Daily Intakes (TDIs) can not be set for HBCD as there is only limited toxicological data available (Committee on toxicity of chemicals in food, consumer products and environment, 2003). The COT did recommend a TDI of 1 mg/kg bodyweight/day for TBBPA (Committee on toxicity of chemicals in food, consumer products and environment, 2004), and the estimated upper bound dietary intakes of TBBPA were well below that value in this study.

Shellfish

Shellfish have been recognised as having the potential for bio-accumulating environmental contaminants, and some species, for example mussels, are often used as early indicators of pollution in local waters. As shellfish are a popular food in many parts of the world including the UK and the authorities are recommending increased consumption of fish and shellfish because of the associated health benefits, it is becoming increasingly important to be able to detect low levels of environmental contaminants, such as HBCD and TBBPA.

Tables III, IV and V give the average recovery corrected whole weight concentrations of the three HBCD diastereoisomers and TBBPA detected in mussel, oyster and scallop gonad and adductor muscle samples. As with the TDS samples, TBBPA was not detected above the LOD (given in Tables III, IV and V) in any of samples. This is consistent with other published studies where quoted concentrations were either below LODs or at very low levels (Winer Sorkina et al, 2003, Food TBBPA is chemically bonded into the polymer matrix, unlike HBCD. This limits the potential for release and may account for the lack of TBBPA in these samples. The most predominant HBCD diastereoisomer in the shellfish was always αHBCD. This is in sharp contrast to the commercial or technical formulations and sediments where γHBCD is dominant, but it does reflect the findings of the TDS study where αHBCD was the dominant diastereoisomer seen in animal and fish based products. αHBCD was detected in samples of mussels, oyster and scallop gonads with the highest concentrations of HBCD detected in mussels from Troustan (8.9 µg/kg, 1.6 µg/kg, 1.5 µg/kg for α, β and γHBCD respectively) and Loch Leven (1.8 µg/kg, 0.42 µg/kg, 0.32 µg/kg) and scallop gonads from Clyde 5 (1.8 µg/kg, 0.24 µg/kg, 0.16 µg/kg). HBCD levels in scallop gonads were always higher than in the corresponding adductor muscles with HBCD only being detected above the LOD in four of the ten scallop adductor samples. This is likely to be due to the higher fat content of the gonads and the lipophilicity of HBCD and TBBPA. The scallop sample Clyde 5 has the highest concentration of HBCD detected in both gonad and adductor muscle. The location of the sampling points has been reported elsewhere (Foods Standard Agency c, Fernandes et al. 2007).

The data generated from the shellfish study was used by the FSA to estimate dietary intakes of HBCD for adults from one weekly portion of shellfish in combination with the rest of the diet, and the results are presented in Table VI. Although dietary surveys of UK consumers in various age groups have been carried out, they were too few to provide robust consumption data in the case of the shellfish species included in this study. Instead dietary intakes of HBCD have been estimated from the measured concentrations assuming an average adult portion size of 70 g for all species. The upper bound dietary intakes of HBCD estimated by this method were 0.16, 0.04 and 0.02 ng/kg body weight/day for α, β and γHBCD respectively for oysters, 1.5, 0.27 and 0.25 ng/kg body weight/day for mussels and 0.29 (0.02), 0.04 (0.01) and 0.03 (0.008) ng/kg body weight/day for scallop gonads (adductor muscles). TBBPA levels were well below the TDI of 1 mg/kg body weight/day. The concentrations determined in this study were of a similar magnitude to those detected in the farmed fish and shellfish survey (Food Standards Agency b) and it is likely that the exposure to these contaminants from the shellfish investigated in this study is similarly not significant when compared to exposure from the rest of the diet.

Conclusions

A method for the extraction, clean-up and detection by LC-MS/MS of individual diastereoisomers (α, β and γ) of HBCD and TBBPA at very low levels is reported in a wide range of food types, as shown by the analysis of TDS samples and a study of shellfish. For both studies TBBPA was not detected above the LOD and concentrations of HBCD detected were generally low with αHBCD being the most predominant diastereoisomer in almost all cases. An assessment of risk carried out by the COT indicated that the levels of HBCD and TBBPA found in these foods were not thought to be of concern to human health.

  . Recovery values were in the ranges 70 -120% for all analytes in both

  (Food Standards Agency d). The estimated upper bound adult dietary intakes of HBCD and TBBPA are presented in Table

  Standards Agency b,

Figure 1 .

 1 Figure captions

Table captions Table I .

 captionsI Whole weight recovery corrected concentration (µg/kg) for αHBCD, βHBCD, γHBCD and TBBPA in 2004 Total Diet Study (TDS) samples, i = indicative as does not pass quality confirmation criteria, < = LODTable II. Estimated upper bound adult dietary intakes (ng/kg) of HBCD from the whole diet in 2004 (Food Standards Agency d)

Table III .

 III Whole weight recovery corrected concentration (µg/kg) for αHBCD, βHBCD,

Table I .

 I

	Table II. Table III. Table IV. Table V. Table VI. Figure 1. Figure 2.
	a						Whole weight recovery corrected Whole weight recovery corrected Whole weight recovery corrected Estimated upper bound adult dietary intakes C H 3 CH 3
		TDS		Br	Whole weight recovery corrected concentration (µg/kg) Estimated upper bound adult dietary intakes Br
	group TDS 7871_BFR4_1_119 100	Food type Food type Sample origin Sample origin Sample origin		αHBCD	βHBCD (ng/kg bodyweight/day) γHBCD concentration (µg/kg) concentration (µg/kg) concentration (µg/kg) (ng/kg bodyweight/day) 16.82	TBBPA F4:MRM of 2 channels,ES-4.527e+004 640.3>78.9
	%	1 group	Bread	O H 14.39		<0.063 αHBCD αHBCD βHBCD γHBCD TBBPA <0.026 <0.036 <0.043 βHBCD γHBCD αHBCD βHBCD γHBCD TBBPA αHBCD βHBCD γHBCD TBBPA αHBCD βHBCD γHBCD OH TBBPA 16.06
				Craigens Pacific Catfirth Clyde 5 Gonad Oysters		0.42 0.17 1.8 0.2 Br	<0.070 <0.040 0.24 0.04 Br	<0.070 0.090 0.16	<0.020 <0.050 <0.22 0.02
	2 Miscellaneous cereals 3 Carcass meat 4 Offal 5 Meat products F o r 1 Bread 2 Miscellaneous cereals 3 Carcass meat 4 Offal F o r Loch Fyne Loch nan Ceol Pacific Shetland F o r Glenuig Bay Linga Lismore F o r Clyde 8 Gonad East Coast Gonad Jura Gonad F o r Mussels Scallops (gonad) Scallops (adductor) F o r Br Br r 14.37 o 7871_BFR4_1_119 % 100 F 0	<0.063 0.15 <0.11 0.11 0.2 0.4 0.5 0.4 0.98 0.30 0.50 0.13 0.32 0.54 1.0 0.38 0.37 1 0.3 0.02 Br TBPPA <0.010 <0.026 <0.043 <0.055 <0.039 0.1 0.06 0.1 0.2 16.07 0.15 0.21 0.18 0.11 <0.070 <0.13 <0.040 <0.030 0.3 0.04 <0.050 <0.036 <0.060 <0.060 <0.054 0.2 0.3 0.2 0.2 0.13 <0.020 <0.043 <0.072 <0.072 <0.065 0.2 0.1 0.2 0.3 <0.040 <0.050 0.15 <0.030 <0.040 0.090 <0.070 0.070 <0.12 0.080 <0.22 0.050 <0.020 0.030 <0.13 0.03 0.01 0.008 Br Br Br F1:MRM of 2 channels,ES-652.3>78.9 3.721e+005 16.83 0.3 m in
	Br 0	6 7 8 5 6 7	13.00	Poultry Fish Oils and fats P e e <0.094 0.24i <0.16 r Meat products 0.3 Poultry 0.5 Fish 2 e r e r Mussels composite 0.62 e r Outer Hebrides Gonad 0.16 e r e r r e P e South Shian Bay Pacific 0.40 P e Loch Leven 1.8 Muckairn (Loch Etive) 0.62 P e Moray Firth Gonad 0.10 Orkney Gonad 0.060 P e P e Br Br Br Br Br P 13.50 14.00 14.50 15.00 15.50 Br e	<0.040 <0.049 <0.065 0.1 0.1 2 0.15 <0.020 0.040 0.42 0.16 0.010 0.010 Br 16.00	<0.054 <0.068 <0.090 0.2 0.2 0.9 0.12 <0.070 <0.010 <0.18 <0.065 <0.081 <0.11 0.2 0.3 0.2 <0.030 <0.020 0.32 <0.010 0.10 <0.070 <0.010 <0.22 <0.020 <0.080 Br Br Br 16.50 17.00 17.50 18.00 m in	Br
		9 10 Sugars and preserves Eggs 11 Green vegetables 12 Potatoes 8 Oils and fats 9 Eggs 10 Sugars and preserves 11 Green vegetables Troustan Wadbister Whalwick South Minch 1/2 Gonad South Minch 3 Gonad αHBCD South Minch 10/11 Gonad Clyde 5 Adductor	<0.19 0.055 0.21 0.057 R e v <0.078 0.030 0.085 0.032 i e 0.6 0.4 0.3 0.1 0.4 0.1 3 1 R e v i e R e v i e 8.9 1.6 0.20i <0.040 0.21 0.040 R e v i e 0.21 <0.020 0.28 <0.020 R R βHBCD R 0.24 <0.020 e e e 0.12 <0.050 v i e v i e v i e	<0.11 0.065 <0.061 0.019i 0.7 0.09 0.2 2 <0.070 0.040 1.5 <0.010 <0.030 <0.070 <0.030 <0.020 <0.13 <0.026 <0.073 <0.017 0.3 0.1 0.2 2 <0.030 γHBCD <0.18 <0.020 <0.18 0.050i <0.22
		13 12	Other vegetables Potatoes Clyde 8 Adductor East Coast Adductor		<0.25 0.4 <0.010 <0.030	<0.11 w 0.2 w w w <0.010 <0.010 w w w	<0.15 0.2 <0.010 <0.010	<0.19 0.2 <0.22 <0.040
		14 15 16 13 14 15	Canned vegetables Fresh fruit Fruit products Other vegetables Canned vegetables Fresh fruit Jura Adductor Moray Firth Adductor Orkney Adductor	0.13 0.29i 0.095 0.2 0.1 0.1 <0.040 <0.030 <0.050	<0.021 0.32 0.058 O 0.086 <0.14 0.12 n l y 0.06 0.08 0.06 0.06 0.05 0.06 O n l O n l O n l <0.020 <0.020 <0.080 <0.035 <0.036 <0.054 0.1 0.07 <0.040 0.030 <0.11 O n l O n l O n l 0.07 y y y <0.080 <0.040 <0.35i y y y
		18 16	Milk Fruit products		<0.28 0.8	<0.12 0.3	<0.16 0.5	<0.19 0.6
			Outer Hebrides Adductor	<0.040	<0.020	<0.030	<0.18
		19 18	Dairy products Milk		<0.12 0.3	<0.050 0.1	<0.070 0.09	<0.084 0.09
			South Minch 1/2 Adductor	0.030	<0.010	<0.010	<0.010
		20 19	Nuts Dairy products		0.17 0.3	<0.065 0.1	<0.090 0.2	<0.11 0.2
			South Minch 3 Adductor	<0.030	<0.030	0.010	<0.21
		20	Nuts			0.1	0.05	0.1	0.05
			South Minch 10/11Adductor 0.060*	<0.010	<0.010	<0.010
							Page 1 of 1 Page 1 of 1 Page 1 of 1 Page 1 of 1 Page 1 of 1 Page 1 of 1 Page 1 of 1

http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.ukFood Additives and Contaminants

Acknowledgements

We gratefully acknowledge the financial support of the Food Standards Agency. The statements and conclusions in this paper are the responsibility of the authors alone and they should not be taken to represent the opinion of the Food Standard Agency.