M W F Nielen

T F H Bovee

H H Heskamp

J J P Lasaroms

M B Sanders

Van Rhijn

M J Groot

Screening for estrogen residues in calf urine: comparison of a 1 validated yeast estrogen bioassay and gas chromatography 2 tandem mass spectrometry 3 4

Keywords: Bioassay, estrogen, urine, screening, GC/MS/MS, residue analysis, steroid 23

Screening for estrogen residues in calf urine: comparison of a validated

Introduction

2

The use of growth promoters for fattening purposes has been banned in the European Union 3 (EU) since 1988 (European Commission, 1996a). Residue analysis of target compounds is 4 carried out by several control laboratories in order to protect the consumer, guarantee fair trade, 5 and to enforce the ban (European Commission, 1996b). Many analyses are carried out in the 6 early stage of the food production chain, in urine and feed samples collected at the farms. The 7 EU regulation as laid down in 96/22/EC (European Commission, 1996a) prohibits the use of 8 substances having hormonal activity and β-agonists. Interestingly, no black-list of substances 9 but any substance having hormonal activity and any beta-agonist is prohibited. Consequently, 10 targeted gas chromatography/mass spectrometry (GC/MS) and liquid chromatography tandem Aliquots of 2 ml of sodium acetate reagent blank, blank calf urine, blank calf urine fortified with 3 17β-estradiol (1 ng/ml), and the samples under investigation, were adjusted to pH 4.8 and 20 µl 4 β-glucuronidase/arylsulfatase (30 and 60 U/ml, respectively) was added. Enzymatic 5 deconjugation was carried out overnight in a water bath at 37 °C. Next, 2 ml of 0.25 M sodium 6 acetate buffer pH 4.8 was added and the hydrolysed sample was subjected to solid phase 7 extraction (SPE) on a C18 column fitted on a vacuum manifold. This column was previously 8 conditioned with 2.5 ml methanol and 2.5 ml sodium acetate buffer. Subsequently, this column 9 was washed with 1.5 ml 10% (w/v) sodium carbonate solution, 3.0 ml water, 1.5 ml sodium 10 acetate buffer pH 4.8, 3.0 ml water and finally with 2 ml methanol/water (50/50 v/v). The column 11 was air-dried and eluted with 4 ml acetonitrile, which was applied to an NH 2 -column, previously 12 conditioned with 3.0 ml acetonitrile. The acetonitrile eluate thus obtained was evaporated to 2 13 ml under a stream of nitrogen gas. A 100 µl part of this extract (equivalent to 100 µl urine) was 14 transferred to a 96 well plate in triplicate and 50 µl water and 2 µl DMSO were added to each 15 well. In order to remove the acetonitrile from this mixture, the plate was dried overnight in a 16 fume cupboard and was then ready to be screened on estrogenic activities with the yeast 17 estrogen bioassay.

19

The yeast cytosensor expressing the human estrogen receptor α (hERα) and yeast enhanced 20 green fluorescent protein (yEGFP) in response to estrogens was developed in-house and 21 described previously (Bovee et al. 2004a, Bovee et al. 2004b). In short, an agar plate containing 22 the selective MM/L medium was inoculated with the yeast ERα cytosensor from a frozen -80 °C 23 stock (20% glycerol v/v). The plate was incubated at 30 °C for 24-48 h and then stored at 4 °C.

24

The day before running the assay, a single colony of the yeast cytosensor was used to inoculate Fluorescence at these time intervals was measured directly in a PerSeptive Biosystems 4 (Framingham, MA, USA) model CytoFluor Series 4000 multi-well plate reader using excitation at 5 485 nm and emission measurement at 530 nm. The t 24 -t 0 differences (mean of the triplicates) 6 were calculated and corrected for the reagent blank data, thus providing the final estrogenic 7 activity data for each sample. The samples are reported "suspect" when the t 24 -t 0 fluorescence 8 measurement exceeds the CCα as determined in the initial validation study [START_REF] Bovee | 25 Validation of a rapid yeast estrogen bioassay, based on the expression of green fluorescent 26 protein, for the screening of estrogenic activity in calf urine[END_REF]); 9 otherwise the samples are reported "compliant". The bioassay is a qualitative screening method, 10 i.e. no concentrations are reported. The densities of the yeast culture at the t 0 and t 24 time 11 intervals are also determined by measuring the OD at 630 nm. This is done from a 12 precautionary principle to check whether a urine sample matrix is toxic for yeast. In routine 13 practice however such cell toxicity never occurred over the last two years. II.

5 can be used directly to inoculate a culture for testing. The next day the culture is ready to be 23 used for screening of the samples, thus requiring some planning the day prior to analysis.

"[Insert

24

Samples can be screened in parallel using a 96-well plate and, without the addition of any

15 (

 15 11 mass spectrometry (LC/MS/MS) methods, which are set-up to the monitoring of a few selected 12 ions or MS/MS transitions, can fulfill the control only to a limited extend (Hewitt et al. 2002; Van 13 Poucke et al. 2002; O'Keeffe et al. 2003; Impens et al. 2003). Moreover, residues of designer 14 steroids and β-agonists will escape from residue control until the original illicit preparations are 15 found, identified by NMR and mass spectrometry, and finally included in the targeted residue 16 analysis methods (Catlin et al. 2004; Nielen et al. 2003). 17 18 Recently we presented a new approach to the search for residues of estrogens in urine, based 19 on a robust yeast reporter gene bioassay and hormonal activity measurement (Bovee et al. 20 2004a, Bovee et al. 2004b). This yeast cell stably expresses the human estrogen alpha receptor 21 (hERα) and yeast enhanced green fluorescent protein (yEGFP) upon exposure to estrogens. In 22 contrast to receptor binding assays, reporter gene bioassays also mimic the transactivation step 23 and can distinguish between receptor agonists and receptor antagonists (Mueller, 2002). 24 Transcription activation bioassays based on human cell lines might be considered even more 25 relevant from a food safety perspective and are often even more sensitive than yeast based 26 bioassays (Sonneveld et al. 2005). However, yeast cells show distinct advantages since they do 27 not produce any steroid receptors until they have been modified to do so. Furthermore yeast 28 cell cultures do not require growth media such as calf serum which might contain steroids. Last 29 not least, yeast cell assays are extremely robust and survive extracts from dirty sample 1 matrices such as urine and feed. Thus robust group-selective bioassays can be constructed 2 which respond selectively to a steroid family such as estrogens while still having good 3 sensitivity. The application of the estrogen bioassay to real urine (or feed) samples is very 4 simple and requires only the addition of the yeast suspension to the sample extract in a 96 well 5 plate, a 4 or 24 h incubation time and measurement in a plate reader. No reagent or cell lysis is 6 required, i.e. measurement at different time points might be easily accomplished, when 7 required. This bioassay is routinely applied as a qualitative screening method in both calf urine 8 and feed sample matrices: only sample extracts showing a fluorescence response beyond the 9 decision limit CCα will be declared suspect for estrogen activity. Subseqently the identity of 10 substances causing the estrogenicity must be determined by conventional residue analysis 11 methods such as GC/MS or using bioassay-directed quadrupole time-of-flight MS (QTOFMS) 12 identification approaches (Nielen et al. 2004; Nielen et al. 2006). The sensitivity of the bioassay 13 is fit for purpose: the decision limit CCα in response units as determined in the initial validation 14 study corresponds with as little as 0.2 ng/ml 17β-estradiol equivalents in calf urine. It is fair to 15 say that this sensitivity is dependent on the relative estrogenic potency, i.e. weaker estrogens 16 than 17β-estradiol such as for example the mycotoxin zearalenone are screened less sensitive. 17 On the other hand, weaker estrogens are less relevant from a hormonal activity point of view 18 and would require relatively high doses anyway. Unfortunately, official residue surveillance plans 19 (European Commission 1996b) within the EU do not differentiate yet between weak and strong 20 hormonal substances; they should be all measured at the more or less equal minimum required 21 performance level (MRPL) of 1-2 ng/ml. Nevertheless, the estrogen bioassay has been fully 22 validated for calf urine (Bovee et al. 2005) and feed samples against the latest EU guidelines 23 (European Commission 2002) and acquired recently an ISO17025 accreditation status in is being used for more than two years now. In this study we present the bioassay and an established GC/MS/MS method for the confirmatory analysis of using a Millipore (Bedford, MA, USA) model Milli-Q Gradient A10 system. 7 Acetonitrile and methanol were from Biosolve (Valkenswaard, The Netherlands). The suc Helix 8 Pomatia β-glucuronidase/arylsulfatase, estrone, ammonium sulphate, dimethyl sulfoxide, 9 sodium acetate and sodium carbonate were obtained from Merck (Darmstadt, Germany). 10 Dithiothreitol, ammonium iodide, 17β-estradiol and 17α-estradiol were purchased from Sigma 11 (St. Louis, MO, USA). 17β-Estradiol-16,16,17-d3 was from C/D/N Isotopes (Pointe-Claire, 12 Canada). N-methyl-N-trimethylsilyl-trifluoroacetamide (MSTFA) was obtained from Pierce 13 (Rockford, IL, USA). Isolute NH 2 solid phase extraction columns (100 mg) were from IST 14 (Hengoed, U.K.) and Bond Elut C18 solid phase extraction columns (500 mg) from Varian Harbor City, CA, USA). Dextrose and yeast nitrogen base without amino acids and without 16 ammonium sulphate were obtained from Difco (Detroit, MI, USA). The minimal cell exposure 17 medium with L-leucine medium (MM/L) consisted of yeast nitrogen base (1.7 g/l), dextrose (20 18 g/l) and ammonium sulphate (5 g/l) and was supplemented with L-leucine (60 mg/l). obtained from a life-time controlled veal calve reference experiment. In 22 short, 21 male and 21 female calves were purchased at the age of 1-3 weeks, raised under 23 representative zootechnical conditions and slaughtered after 26 weeks. The animals were fed 24 via an automated milk system using regular milk replacer. According to histopathology of the 25 prostates and the Bartholin glands at slaughter, no intentional (or unintentional) hormone 26 treatment was detected (Groot et al. 2006). 126 urine samples were random collected during 27 the experiment at the age between 9 and 26 weeks and analysed by both the bioassay and the 28 GC/MS/MS protocols.

  25 10 ml of selective MM/L medium. This culture was grown overnight at 30 °C with vigorous orbital 26 shaking at 225 rpm. At the late log phase, the yeast ERα cytosensor was diluted (1:10) in MM/L.27For exposure in 96 well plates, aliquots of 200 µl of this diluted yeast culture were pipetted into 28 well, already containing the extracts of the urine samples. A 17β-estradiol dose-response 1 curve in DMSO was included in each exposure experiment. Each urine sample extract and each 2 17β-estradiol stock were assayed in triplicate. Exposure was performed for 0 h and 24 h.

  3

  of sodium acetate reagent blank, blank calf urine, blank calf urine fortified with 17 17β-estradiol and other estrogens at 0.5, 1.0, 2.0, 5.0 and 10 ng/ml, and the urine samples 18 under investigation, were spiked with deuterium-labelled 17β-estradiol as internal standard at 2 19 ng/ml. The samples were enzymatically deconjugated and subjected to solid phase extraction 20 as described in the bioassay procedure, except for the elution solvent of the C18 and NH 2 21 extraction columns which was methanol instead of acetonitrile. The extracts thus obtained were 22 redissolved and fractionated by preparative reversed phase gradient LC on a 250 x 3.0 mm I.D. 23 Lichrocart (Merck) column packed with 5 µm C18 RP-Select B material and equipped with a 24 Lichrocart 4-4 guard column packed with similar material. The two mobile phases used consisted 25 of (A) methanol/water (10:90) and (B) methanol/water (90:10) and the flow was 0.4 ml/min.26Following an isocratic period of 10 min at 65% B a steep linear gradient was started towards 27 95% B at 12 min, followed by a final isocratic step of another 9 min. The steroid fraction was 28 evaporated to dryness under a stream of nitrogen gas at 45 °C, redissolved in dry ethyl acetate, and derivatised using so-called MSTFA++ reagent (a mixture of dithiothreitol, 1 ammonium iodide and MSTFA) for 15 minutes at 60 °C. Finally 2 µl of the silylated steroids 2 were injected into a GC/MS/MS system consisting of an Agilent (Palo Alto, CA, USA) model 3 6890N capillary gas chromatograph equipped with a splitless injector, helium as carrier gas, and 4 a 30 m x 0.25 mm I.D. Restek (Bad Homburg, Germany) model Rtx-CL Pesticides (df 0.25 µm) 5 column, coupled with a Micromass (Manchester, UK) model Quattro Micro GC/MS/MS system. 6 Following an initial temperature of 130 °C for two minutes, the GC oven was programmed 7 towards 250 °C at a rate of 12 °C/min, followed after 3 min by a second ramp towards 300 °C at a 8 rate of 7.5 °C/min. The total analysis time per sample injection was 35 min. The mass 9 spectrometer was operated in the Electron Impact (EI) ionisation mode at 70 eV, using an 10 interface temperature of 275 °C, a source temperature of 180

Food 27 28

 27 20were calculated and corrected for recovery losses using the isotope dilution method and a 21 calibration curve based on matrix-matched standards, i.e. blank urine samples spiked with 0, 0.5, 22 1.0, 2.0, 5.0 and 10 ng/ml of a steroid mixture. the estrogen bioassay27A general concern when applying bioassays for screening is the occurrence of biologically 28 inactivated substances in urine matrices. However in the experimental procedure inactivated 29 Page 8 of 22 http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk II metabolites are reconverted into their corresponding phase I metabolites, thanks to the 1 enzymatic sample pretreatment step. In a previous study[Bovee et al. 2004b] it was shown that 2 phase I metabolites such as 17α-estradiol, estrone, estriol and hydroxylated estrogens do give 3 a response in the bioassay, but they require a higher concentration for detection. In hormone 4 treatment of cattle the urinary profile usually contains a mixture of phase II metabolites of the 5 parent drug and its phase I metabolites. Since the bioassay provides an additive measurement 6 of alle estrogenic residues and metabolites (having different relative estrogenic potencies) the 7 chance of overlooking illegal treatment is relatively low as compared to other screening assays 8 such as highly specific immuno assays.The estrogen bioassay is routinely applied in our 9 laboratory for the screening of urine samples for more than two years now. Cell toxicity caused 10 by matrix components in the urine extract was never observed. A control chart is given in Figure it can be seen that negative reagent blank and calf urine control samples were 15 compliant during this period, except for two blank urine cases which were false suspect (slightly 16 above CCα). The positive calf urine control samples (blank urines fortified with 1 ng/ml 17β-17 estradiol) were always found suspect in the same period, i.e. false compliant results were not 18 observed at all. Despite the inherent variability caused by variable analyte recovery and natural 19 fluctuations in the biological assay, the data presented here clearly show that application of 20 hormone bioassays in routine control is feasible, even on the long-term, provided that the assay 21 is applied as an on/off qualitative screening method rather than a quantitative assay. These 22 results from long-term routine practice are in accordance with expectations from the initial 23 validation study[START_REF] Bovee | 25 Validation of a rapid yeast estrogen bioassay, based on the expression of green fluorescent 26 protein, for the screening of estrogenic activity in calf urine[END_REF]. Moreover, these findings support the ruggedness and 24 stability of the entire assay including sample preparation, cell culturing, cell growth and 25 detection; otherwise the control sample results would not be so consistent over such a long time 26 period.Comparison between the bioassay and GC/MS/MS results29 (/MS) is the routine screening and confirmatory analysis method for steroids in urine 1 samples in many veterinary residue control and sports doping laboratories worldwide. Typically, 2 following a liquid-liquid or solid phase extraction protocol the extracts are fractionated, silylated 3 and analysed. The performance characteristics of the GC/MS/MS versus the bioassay 4 screening of natural estrogens in urine are given in Table

  11weeks were subjected to both the bioassay and the GC/MS/MS protocols. The results of both 12 methods are summarised in Figure2. Again, none of the urine samples caused any cell toxicity 13 in the bioassay, in accordance with our two years experience with this estrogen bioassay. The 14 negative urine bioassay controls were compliant and the positive (1 ng/ml 17β-estradiol) urine 15 controls were screened "suspect" in all bioassay series. In the GC/MS/MS series the negative 16 controls were compliant and the fortified urine control samples were always confirmed as non-17 compliants according to the EU criteria (European Commission 2002). According to the 18 GC/MS/MS method 71 out of the 126 calf urine samples were compliant for estrogens, i.e. all 19 estrogens included in this instrumental multi-residue method were below 1 ng/ml. screening 67 out of 126 were screened compliant for estrogen activity. Only 4 24 out of 71 (5.6 %) might be considered false-suspects in comparison with the GC/MS/MS results, 25 but it should be kept in mind that these four urine samples might really contain (a mixture of) low /MS/MS method 55 urine samples were found to contain estrogens at a level of 1 2 ng/ml or more. In all cases the natural estrogen 17α-estradiol was identified (concentrations are 3 given in Figure2), occasionally accompanied by estrone. The presence of these natural 4 estrogens in urine from individual calves is not unexpected when they reach the age of 20comparison of the non-compliant samples found by the quantitative GC/MS/MS 8 confirmatory analysis method and the suspect samples found by the qualitative bioassay 9 screening method, one should consider the sensitvity of the bioassay for these estrogens. 10 Bioassay response curves for 17α-estradiol and estrone were recorded in triplicate and are 11 shown in Figure 3, together with the reference curve for 17β-estradiol. in good agreement with the previous literature data: the sensitivity of the 15 estrogen bioassay is dependent on the estrogenic potencies of the analytes present. According 16 to literature the relative estrogenic potency (REP) of 17α-estradiol and estrone versus 17β-17 estradiol is 0.09 and 0.2, respectively (Bovee et al., 2004b), similar to the data in Figure 3. The 18 decision limit CCα and the detection capability CCβ of the bioassay were determined in the 19 validation study (Bovee et al., 2005), but for 17β-estradiol and not for the natural estrogens 17α-20 estradiol and estrone (cf.

3

  might expect more consistency between GC/MS/MS and bioassay data: at and beyond the 4 predicted CCβ of 17α-estradiol, i.e. above 5-11 ng/ml (depending on whether the calculated or 5 experimentally determined CCβ 17β-estradiol has been used for the prediction) at least 95% 6 consistency might be expected provided the CCβ data of 17β-estradiol from the bioassay 7 validation study[START_REF] Bovee | 25 Validation of a rapid yeast estrogen bioassay, based on the expression of green fluorescent 26 protein, for the screening of estrogenic activity in calf urine[END_REF]) and the REP data of 17α-estradiol(Bovee et al. 2004b) are 8 valid and, moreover, provided the recovery is extremely reproducible. According to Figure2this 9 expectation is valid except for two urine samples, one containing 5.5 ng/ml 17α-estradiol 10 (rounded off to 6 ng/ml in Figure2) and a second one containing 10 ng/ml 17α-estradiol by 11 GC/MS/MS. The discrepancy observed between the GC/MS/MS and the bioassay data at the 12 5.5 ng/ml level can be easily explained when one takes into account that the concentration as 13 determined by the GC/MS/MS method was corrected for incomplete recovery using deuterium-14 labelled estradiol as internal standard. It should be noted that the predicted CCβ of 17α-15 estradiol ranges from 5 to < 11 ng/ml, depending on whether the calculated or experimentally 16 verified CCβ of 17β-estradiol was taken; only the experimentally determined value includes 17 recovery losses. The bioassay did show increased fluorescence for the 5.5 ng/ml 17α-estradiol 18 sample but the level was just below the CCα treshold for being qualified as "suspect". 19 According to GC/MS/MS the urine sample containing 10 ng/ml 17α-estradiol also contained a 20 low level of estrone which should have triggered the bioassay in addition to the 17α-estradiol 21 level. The GC/MS/MS reconstructed chromatograms shown in Figure 4 clearly indicate the 22 presence of these compounds in this particular urine sample. did not show any increased fluorescence so the bioassay result for this 26 specific sample suggests a real false-compliant case (1 out of a total of 126 samples). Apart 27 from a human error such as sample interchange no other major discrepancy sources are to be 28 sample preparation is quite similar for both methods. The original incurred 1 urine sample was re-analysed by both the bioassay and the GC/MS/MS in 6-fold, but nine 2 months later. In all six replicates the bioassay showed a strong signal and the sample was 3 screened suspect without any doubt and in full agreement with the 10 ng/ml GC/MS/MS data, 4 even after 9 months. Obviously the stability of calf urine samples under appropriate storage 5 conditions is much longer than the ≥90 days determined in the validation study (Bovee et al. 6 2005). From the results of the re-analysis it was concluded that the apparent false-negative 7 urine sample was most likely caused by a human error. 8 9 Currently, the bioassay screening is limited to calf urine: older bovines produce quite a lot of 10 endogenous 17α-estradiol and estrone and will cause too many false suspect urine data. We 11 are currently investigating the option of selective removal of 17α-estradiol and estrone from 12 bovine urine in order to extend the scope of this method to older animals. of a previously validated estrogen bioassay is in full accordance with 17 expectations. The results of negative and positive calf urine control samples analysed in a 18 period covering more than two years indicate a very good ruggedness over time. In a direct 19 comparison with an established GC/MS/MS steroid analysis method the estrogen bioassay 20 showed a low percentage (5.6%) of potential false suspect results. The bioassay screening can 21 be considered fast and simple: plates with yeast cells are stable at 4 ºC for over one month and 22

Figure 1 .Figure 2 .

 12 Figure 1. Control chart of the routine urine application of the bioassay, covering the period 2003-

Figure 3 .

 3 Figure 3. Response curves of the yeast estrogen bioassay after a 24 h exposure to 17β-

Table II

 II

	6	about here]"
	7
	8	In this study we assumed the GC/MS/MS confirmatory analysis method to perform beyond
	9	reasonable doubt, which is justified by the precision and accuracy data given in Table II, and
	10	made a comparison with the yeast estrogen bioassay screening method. 126 calf urine samples
		collected during a controlled reference experiment at different time points between 9 and 26

Table II

 II

	1
	2	(CCα estrone ). Indeed from the 38 GC/MS/MS results containing 1 to 3 ng/ml 17α-estradiol only a
		few samples were screened suspect in the bioassay. Beyond 3 ng/ml 17α-estradiol in urine one
		F o r
		P
		e
		e r
		R
		e
		v i e
		w
	21 22	). However, the CCα 17α-estradiol , CCβ 17α-estradiol (and CCα estrone and CCβ estrone ) can be predicted from the 17β-estradiol data and the REP's, as follows: the O n l
	23	CCα 17β-estradiol in fluorescence response units corresponds with 0.22 ng 17β-estradiol equivalents y
	24	per ml (Bovee et al., 2005). The CCβ 17β-estradiol as calculated from this CCα was 0.44 ng/ml, while
	25	the experimentally verified CCβ 17β-estradiol was < 1 ng 17β-estradiol equivalents per ml (Bovee et
	26	al., 2005). When these CCβ and CCα values of 17β-estradiol are divided by the REP-values of
	28

17α-estradiol and estrone

(Bovee et al., 2004b)

, a prediction of the CCα and CCβ is obtained 27 for 17α-estradiol and estrone. By doing so a bioassay response might be expected for 17α-

Table I .

 I MS/MS conditions of the MRM acquisition used in the GC/MS/MS analysis of TMS

		Food Additives and Contaminants		Page 16 of 22
	1 1 1 1	screening with the estrogen bioassay will significantly reduce the sample workload of the 17b-Estradiol 416 > 285 416 > 326 12
	2 2 2 2	instrumental GC/MS/MS analysis method. Tetrahydrogestrinone: discovery, synthesis, and detection in urine. Rapid Communications in Mueller, S.O. 2002. Overview of in vitro tools to assess the estrogenic and antiestrogenic method for the detection of anabolic steroids in bovine urine with liquid chromatography-tandem 17b-Estradiol-d3 (ISTD) 419 > 285 -10
	3 3 3 3	Mass Spectrometry 18:1245-1249 activity of phytoestrogens. Journal of Chromatography B 777:155-165. mass spectrometry. Journal of Chromatography B 772:211-217. 17a-Ethyl-5b-estrane-3a,17b-diol 421 > 331 421 > 241 17b-Testosterone 432 > 209 432 > 133	10 15
	4 4 4 4	In the samples found non-compliant by GC/MS/MS the bioassay responded as predicted on the Methenolone 208 > 119 208 > 193 15
	5 5 5 5	basis of the relative estrogenic potency of the analytes involved. Indeed the bioassay is less European Commission. 1996a. Council directive 96/22/EC of 29 April 1996 concerning the Nielen, M.W.F.; Elliott, C.T.; Boyd, S.A.; Courtheyn, D.; Essers, M.L.; Hooijerink, H.; van 5a-Androstane-17a-methyl-3b,17b-diol 435 > 255 435 > 345 10
	6 6 6 6	sensitive for weak estrogens than GC/MS/MS, but perhaps that is more relevant than findings of prohibition on the use in stockfarming of certain sunstances having a hormonal or thyreostatic Bennekom, E.O.; Fuchs, R.E.M. 2003. Identification of an unknown b-agonist in feed by liquid 17a-Ethinylestradiol 425 > 193 300 > 232 15 17a-Methyltestosterone 446 > 301 301 > 169 12
	7 8 9 7 8 9 7 8 9 7 8 9	F o r very low levels of inactive substances. After all, the legislative fundament laid down in 96/22/EC (European Commission, 1996a) bans substances having hormonal activity. F o r action and of beta-agonists, and repealing directives 81/602/EEC, 88/146/EEC and 88/299/EEC. Official Journal of the European Communities, L125:3-9. F o r chromatography/bioassay/quadrupole time-of-flight tandem mass spectrometry with accurate mass measurement. Rapid Communications in Mass Spectrometry 17:1633-1641. F o r 17a-Methyltestosterone-d3 (ISTD) 449 > 301 -10 F Norethandrolone 446 > 287 287 > 155 10 o Norgestrel 456 > 316 456 > 301 12 r Chloroandrostenedione 464 > 429 464 > 169 15
	10 11 12 13 14 15 10 11 12 13 14 15 10 11 1 2 12 13 15 14 3 4	P e e r R P e e r R European Commission. 1996b. Council directive 96/23/EC of 29 April 1996 on measures to monitor certain substances and residues thereof in live animals and animal products and repealing directives 85/358/EEC and 86/469/EEC and decisions 89/187/EEC and 91/664/EC. Official Journal of the European Communities, L125:10-32. European Commission. 2002. Commission decision 2002/657/EC of 12 August 2002 P e e r R Nielen, M.W.F.; van Bennekom, E.O.; Heskamp, H.H.; van Rhijn, J.A.; Bovee, T.F.H.; Hoogenboom, L.A.P. 2004. Bioassay-directed Identification of Estrogen Residues in Urine by Liquid Chromatography Electrospray Quadrupole Time-of-Flight Mass Spectrometry. Analytical Chemistry 76:6600-6608. Nielen, M.W.F.; Bovee, T.F.H.; van Engelen, M.C.; Rutgers, P.; Hamers, A.R.M.; van Rhijn, J.A.; P e e r R Fluoxymesterone 480 > 335 390 > 375 12 P e R e r
	16 16 16	e e implementing council directive 96/23/EC concerning the performance of analytical methods and e Hoogenboom, L.A.P. 2006. Urine Testing for Designer Steroids by Liquid Chromatography with e derivatised calf urine extracts. e
	17 18 19 20 17 18 19 20	v i e w v i e w the interpretation of results. Official Journal of the European Communities, L221:8-36. Groot, M.J., Nielen M.W.F. 2006. The ultimate veal calf reference experiment: histology and chemical analysis. Presented at the fifth International Symposium on Hormone and Veterinary v i e w Androgen Bioassay detection and Electrospray Quadrupole Time-of-Flight Mass Spectrometry Identification. Analytical Chemistry 78:424-431. O'Keeffe, M.J.O.; Martin, S.; Regan, L. 2003. Validation of a multiresidue liquid v i e w Component Ion transition for screening (m/z) Ion transition for confirmation (m/z) Collision energy (eV) Hexestrol 207 > 179 207 > 163 v i e 10 Dienestrol 410 > 395 410 > 179 10 cis-Diethylstilbestrol 412 > 383 412 > 217 15 w
	21 22 23 24 21 22 23 24	O n l y O n l y Hewitt, S.A., Kearney, M., Currie, J.W., Young, P.B., Kennedy, D.G. 2002. Screening and Drug Residue Analysis, May 16-19, Antwerp, Belgium. confirmatory strategies for the surveillance of anabolic steroid abuse within Northern Ireland. O n l y chromatography-tandem mass spectrometric method for the quantitation and confirmation of corticosteroid residues in urine, according to the proposed SANCO 1085 criteria for banned substances. Analytica Chimica Acta 483:341-350. O n l y trans-Diethylstilbestrol 412 > 383 412 > 217 15 Ethylestrenol 270 > 241 241 >145 15 Estrane(5a)-3b,17a-diol 332 > 201 332 > 291 5 Equol 386 > 192 386 > 267 O n l 10 17a-Nortestosterone 418 > 194 418 > 182 15 y
	25 25 25	Analytica Chimica Acta 473:99-109. Sonneveld, E.; Jansen, H.J.; Riteco, J.A.C.; Brouwer, A.; Van der Burg, B. 2005. Development 5b-Androstane-17a-methyl-3a,17b-diol 270 > 255 435 > 345 10 Estrone 414 > 155 399 > 155 15
	26 26 26	reagent, fluorescence is measured by a simple plate reader after 4 or 24 hours. It is true that of androgen-and estrogen-responsive bioassays, members of a panel of human cell-line based 17a-Estradiol 416 > 285 416 > 326 12
	27 27 27	recombinant yeast requires special laboratory facilities, but for this recombinant yeast only an Impens, S.; Courtheyn, D.; De Wasch, K.; De Brabander, H.F. 2003. Faster analysis of anabolic highly selective steroid-responsive bioassays. Toxicological Sciences 83:136-148. 17b-Nortestosterone 418 > 194 418 >182 15
	28 28	steroids in kidney fat by downscaling the sample size and using gas chromatography-tandem 17b-Nortestosterone-d3 (ISTD) 421 > 182 -15
	29 29	mass spectrometry. Analytica Chimica Acta 483: 269-280. 17a-Testosterone 432 > 209 Methandriol 253 > 197	432 > 133 268 > 253	Thus 15 15
		14 16

ML1-category biohazard laboratory is needed. The costs of bioassay screening are so low that 28 one can even apply it as an HPLC detector (Nielen et al. 2004; Nielen et al. 2006).

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

Table II .

 II Performance characteristics of the analysis of natural estrogens in urine by GC/MS/MS

5

versus the yeast estrogen bioassay data in literature

[START_REF] Bovee | 25 Validation of a rapid yeast estrogen bioassay, based on the expression of green fluorescent 26 protein, for the screening of estrogenic activity in calf urine[END_REF]

).

  Figure 4. Reconstructed GC/MS/MS chromatograms of the urine sample containing 2 approximately 10 ng/ml of 17α-estradiol. For conditions, see Materials and Methods and TableI.

						Food Additives and Contaminants				Page 22 of 22
	1
	3
		100
		%	17a-estradiol								m/z 416>326
		12.00 0	12.25	12.50	12.75	13.00	13.25	13.50	13.75	14.00	14.25	14.50	14.75	15.00
		% 100 12.00 0 100 %	17a-estradiol F 12.25 12.50 o 12.75 r i.s. (17b-estradiol-d3)	13.00	13.25	13.50	13.75	14.00	14.25	m/z 416>285 14.50 14.75 m/z 419>285	15.00
		12.00 0	12.25	12.50	P 12.75 13.00	13.25	13.50	13.75	14.00	14.25	14.50	14.75	15.00
		12.00 0 % 100 estrone 12.25	12.50	e r 12.75 13.00 13.25 e	13.50	13.75	14.00	14.25	14.50 m/z 414>155 14.75	15.00
	4 5	% 100 12.00 estrone 12.25 0	12.50	12.75	13.00	R 13.25 13.50 e e 13.75 14.00 i v	14.25	m/z 399>155 14.50 14.75	Time 15.00
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Food Additives and Contaminants

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levels of estrogens because of the additive bioactivity measurement. No attempts were made to

Acknowledgements 10 This project was financially supported by the Dutch Ministry of Agriculture, Nature and Food 11 Quality (project nr. 72027.01).

12 13


Sarah ; Pastorelli
email: sarah.pastorelli@jrc.it

Sandro Valzacchi

Ana Rodriguez

Catherine Simoneau

Rodriguez

SPME analytical method for the determination of Hexanal in hazelnuts as indicator of the interaction of active packaging materials with food aroma compounds

Keywords: Packaging active packaging, Volatiles SPME, hexanal, lipid oxidation, oxygen scavengers http://mc.manuscriptcentral.com/

SPME analytical method for the determination of Hexanal in hazelnuts as

Introduction

Food products with high fat content, such as hazelnuts and nuts in general, are susceptible to rancidity because of lipid oxidation, which involves the development of off-flavours that make the product undesirable for the consumers. As it is well known, the oxidation process is accelerated by different factors such as light and temperature. In order to delay the oxidation and to extend the product shelf-life, several approaches have been developed by the food industry. Special packaging techniques, such as modified atmosphere, oxygen-barrier packaging material and active packaging (oxygen scavengers) [START_REF] Lee | Accelerated shelf life testing of whey-protein-coated peanuts analyzed by static headspace gas chromatography[END_REF] as well as the addition of natural or synthetic antioxidants have been recently investigated [START_REF] Stashenko | SPME determination of volatile aldehydes for evaluation of in-vitro antioxidant activity[END_REF].

Hexanal was found to be a good marker of the oxidative rancidity since it is one of the most abundant products of the oxidation of fats and its content increases during storage [START_REF] Stashenko | SPME determination of volatile aldehydes for evaluation of in-vitro antioxidant activity[END_REF][START_REF] Lee | Accelerated shelf life testing of whey-protein-coated peanuts analyzed by static headspace gas chromatography[END_REF][START_REF] Goodridge | Solid phase microextractiongas chromatography for quantifying headspace hexanal above freeze-dried chicken myofibrils[END_REF][START_REF] Brunton | A comparison of solid-phase microextraction (SPME) fibres for measurement of hexanal and pentanal in cooked turkey[END_REF][START_REF] Shahidi | Headspace volatile aldehydes as indicators of lipid oxidation in foods[END_REF][START_REF] Jensen | Storage stabilities of pork scratchings, peanuts, oatmeal and muesli: comparison of ESR spectroscopy, headspace-GC and sensory evaluation for detection of oxidation in dry foods[END_REF]. It is the main aldehyde formed during the oxidation of linoleic, gamma-linolenic and arachidonic acids [START_REF] Shahidi | Headspace volatile aldehydes as indicators of lipid oxidation in foods[END_REF].

Different techniques for volatile isolation and pre-concentration, such as dynamic headspace, purge and trap [START_REF] Cadwallader | Analysis of volatile components in fresh grapefruit juice by purge and trap/gas chromatography[END_REF], and static headspace [START_REF] Romeu-Nadal | Headspace gas chromatographic method for determining volatile compounds in infant formulas[END_REF]) have been described in the literature. Although they are simple and fast, these methods present certain drawbacks. The first two of these, are not easy to automate and are time-consuming and on static headspace techniques can lack of sensitivity [START_REF] Goodridge | Solid phase microextractiongas chromatography for quantifying headspace hexanal above freeze-dried chicken myofibrils[END_REF][START_REF] Snow | Head-space analysis in modern gas chromatography[END_REF]. To overcome these disadvantages SPME has been successfully applied in food analysis to evaluate the volatile profiles in different foodstuffs: fruits [START_REF] Augusto | Screening of Brazilian fruit aromas using solid-phase microextraction gas chromatography-mass spectrometry[END_REF][START_REF] Lourdes-Cardeal | Analysis of volatile compounds in some typical Brazilian fruits and juices by SPME-GC method[END_REF], meat [START_REF] Ramirez | Effect of the type of frying culinary fat on volatile compounds isolated in fried pork loin chops by using SPME-GC-MS[END_REF]), vinegar (Natera-Marin et al. 2002), olive oil (Garcia-Gonzalez et al. 2004), soybean [START_REF] Boué | Identification of volatile compounds in soybean at various developmental stages using solid phase microextraction[END_REF], truffle [START_REF] Diaz | Truffle aroma analysis by headspace solid phase microextraction[END_REF] and also to analyse hexanal in several matrices: turkey [START_REF] Brunton | A comparison of solid-phase microextraction (SPME) fibres for measurement of hexanal and pentanal in cooked turkey[END_REF], powder infant milk formula [START_REF] Fenaille | Comparison of mass spectrometry-based electronic nose and solid phase microextraction gas chromatography-mass spectrometry technique to asses infant formula oxidation[END_REF]) and freeze-dried chicken [START_REF] Goodridge | Solid phase microextractiongas chromatography for quantifying headspace hexanal above freeze-dried chicken myofibrils[END_REF].

The purposes of the present paper were to develop a simple and fast SPME-GC-FID method to determine hexanal and to evaluate the effect of the oxygen scavengers on the oxidation of hazelnuts samples stored under controlled conditions.

Materials and methods

Sampling

Powdered hazelnuts packed with a transparent film were purchased from a local supermarket. A gas chromatography-flame ionization detector (GC-FID) analysis was performed immediately after being acquired. Then they were stored under controlled conditions of light and temperature in 20 mL hermetically closed flasks with and without oxygen absorbers sachets added to the packaging until analysis.

Reagents and Analytical standards

Hexanal was purchased from Sigma-Aldrich (Steinheim, Germany) with purity of 98%.

Two stock standard solutions of 500 mg/L of hexanal were prepared by using Milli-Q water and triacetin as solvents. Working solutions employed were prepared by diluting different amounts of the stock standard solution in Milli-Q water and triacetin respectively. Both solutions were stored at 4°C. Ultra pure water was obtained using a Milli-Q filter system (Millipore, Bedford, MA, USA) and triacetin was supplied from Sigma-Aldrich (Steinheim, Germany).

SPME procedure

The SPME holder for manual sampling and the commercial fibres tested in this study were purchased from SUPELCO (Bellefonte, PA, USA). Five fibres with different coating materials were examined: PDMS with 100 µm thickness; CAR/PDMS with 75 µm thickness, PDMS/DVB with 65 µm thickness, CAR/DVB with 65 µm thickness and DVB/PDMS/CAR with 50-30 µm thickness. Prior to their use they were conditioned by inserting them into the GC injector according the supplier's instructions summarized in Table I.

One mL of the standard solution or 0.1 g in the case of the hazelnuts samples were placed in a 20 mL vial that was hermetically sealed with a PTFE-coated silicone septum and analysed by SPME-GC. A small magnetic stirring bar was added to the vial before it was capped. Then the vials were placed in an aluminium thermostated block at 60°C for 10 min to reach the equilibrium with the headspace. After equilibrium time the SPME fibre was exposed to the headspace of the sample at 60°C for 10 min (extraction time). Then the fibres were directly inserted into the injector port of the GC for thermal desorption at the temperature reported in table I, during 15 min.

To ensure that all impurities were removed blank runs were conducted between sample analysis. Each sample extraction was carried out in triplicate.

Gas chromatography

Analyses were performed on a 5890 Hewlett-Packard gas chromatograph equipped with a flame ionization detector (FID). The GC system was operated using splitless injection mode. A 0.75 mm i.d. narrow-bore glass liner (Supelco, Bellefonte, USA) was used to prevent peak broadening (Vas and Vékey 2004) and consequently to improve the resolution of the analysis. A DB-wax fused capillary column (30 m 0.25 mm ID, 0.5 µm) was used for hexanal analysis. Operating conditions were as follows: injector temperature was set between 240-300°C depending on the fibre used and detector temperature was kept at 350°C. The ramp temperature was initially set at 50°C, then raised at the rate of 10°C/min to100°C, then increased at 20°C/min until 200°C and held for 7min. The carrier gas was helium with a flow rate of 1.2 mL/min. A Hewlett Packard 6890 gas chromatograph equipped with a Hewlett Packard 5973 mass detector working in electronic impact ionization mode in full scan acquisition mode was used for hexanal identification. The chromatographic conditions were the same as those specified for the GC-FID system. Hexanal was identified by the library

Results and Discussion

SPME-GC method Optimisation

In developing gas chromatographic method several temperature ramps were studied, the selected ramp was that provided the best resolution in a shorter time. Triacetin and Milli-Q water were evaluated as solvents for standard solutions. Hexanal showed considerable instability in water, however with triacetin good results in terms of reproducibility were obtained, and for this reason triacetin was chosen as solvent.

Furthermore, as triacetin has a higher boiling point than hexanal, a good chromatographic separation without interferences was achieved.

The SPME sampling procedure depends on several variables such as equilibrium and extraction time and temperature, the amount of the sample, and the kind of the fibre coating. In order to optimise all these parameters, several experiments were conducted.

Initially, a hexanal standard solution was used to fix time and temperature conditions, then a series of assays with hazelnuts samples were conducted taking into account the effect of the matrix. A PDMS 100 µm fibre was used to carry out the preliminary trials since it is the most often used due to its physicochemical properties, it is also very rugged and recommended for the extraction of volatile flavour compounds (Vas and [START_REF] Kataoka | Applications of solid-phase microextraction in food analysis[END_REF]. In a first series of assays the parameter studied was the equilibrium temperature. Different values were tested (50, 60, 70 and 80°C) keeping equilibrium time (10 min) and extraction time (10 min) fixed. Under these conditions the best results were found at 60 and 70°C, so that we selected the lower temperature.

Once the temperature was optimised the equilibrium time was studied ranging from 5 to 60 min; it was found that 10 min was enough to reach the equilibrium, therefore an equilibration time of 10 min was selected for successive analyses. Three different extraction times, were also evaluated: 5, 10 and 20 min. Best results were achieved at 10 min. These results are in accordance with those reported by Ezquerro et al. 2003, where it is indicated that the extraction time depends on the compound, in general, for small compounds such as the hexanal after 10-20 min of exposure of the fibre to the headspace the signal (peak area) decreased.

In order to establish the optimal sample amount 0.1 g, 1 g, 10 g and 15 g of ground hazelnuts were assayed, and 0.1 g was considered a suitable sample amount to produce quantitative results. Finally, the effect of the dilution of the sample with Milli-Q water (1mL) and the addition of a saturated salt solution of NaCl were also evaluated. As it has been reported in the literature (Pino et al. 2002) the addition of the salt to the sample could modify the nature of the matrix and the extraction efficiency since this addition can affect the partition coefficient of the analytes, however in terms of improvement of analyte extraction from the sample no significant differences were observed so subsequent analyses were carried out with dry sample. for the equilibrium and to facilitate the transfer of the analyte from the matrix to the fibre coating material (Vas and Vékey 2004;[START_REF] Pillonel | Rapid preconcentration and enrichment techniques for the analysis of food volatile[END_REF]. Five commercial available fibres (PDMS, CAR/PDMS, PDMS/DVB, CAR/DVB and DVD/CAR/PDMS) were compared. The CAR/PDMS fibre had the highest sensitivity. This result is in agreement with those reported by [START_REF] Augusto | Screening of Brazilian fruit aromas using solid-phase microextraction gas chromatography-mass spectrometry[END_REF][START_REF] Brunton | A comparison of solid-phase microextraction (SPME) fibres for measurement of hexanal and pentanal in cooked turkey[END_REF][START_REF] Natera-Marin | Headspace solid-phase microextraction analysis of aroma compounds in vinegar validation study[END_REF] pointed out that the high efficiency of this coating could be attributed to the high porosity that provides a strong adsorption. Furthermore, [START_REF] Ezquerro | Development of a headspace solid-phase microextraction-gas chromatography-mass spectrometry method for the identification of odour-causing volatile compounds in packaging materials[END_REF] reported that for low molecular mass compounds the CAR/PDMS provides good results and [START_REF] Diaz-Maroto | Fast screening method for (SIM)[END_REF] obtained high recoveries when using a fibre containing a porous coating. According to the method proposed by [START_REF] Augusto | Screening of Brazilian fruit aromas using solid-phase microextraction gas chromatography-mass spectrometry[END_REF], the inter fibres comparison (figure 1) was made calculating the normalized extraction efficiency (N i,x ) defined as N= 100* A ix /A iCAR/PDMS where A ix is the hexanal area analyzed with the fibre x and A i CAR/PDMS is the corresponding area with the most efficient fibre (CAR/PDMS).

The experiments were performed in triplicate.

"[Insert Figure 1 about here]"

Performance characteristics

A calibration curve was carried out using a series of six hexanal standards of known concentration. Parameters of linearity were the follow: -388.05 (intercept); 974216 (slope); 0.999(r 2 ); and 0,25-2,5 ng/mL (range). Another calibration line was constructed by spiking hazelnuts samples. 10 µl of a triacetin solution with different hexanal quantities were added to the samples. The equation was Y= 506322x-120.94, the 10 determination coefficient and the linearity were 0.997 and 0,25-2,5 ng/mL respectively. Detection limit calculate in accordance with the Subcommittee on environmental analytical chemistry (ACS) guidelines (defined as a signal three times the height of the noise level) was 0.08 ng/mL. The value obtained is lower than the LOD obtained by [START_REF] Romeu-Nadal | Headspace gas chromatographic method for determining volatile compounds in infant formulas[END_REF] in infant formulas.

Repeatability was estimated as relative standard deviation (RSD) for the determination of six extracts, from the same oxidized sample with an hexanal content of 0.25 ppb, each prepared separately, was 5.32%.

Evaluation of oxygen scavengers in the oxidation process.

In the first tests to evaluate the effect of the oxygen scavenger on the oxidation process the headspace of the vial containing the hazelnuts with and without the oxygen absorber sachets was analysed. The O 2 content was measured using a Chek Mate 9900 Dansensor (Milano, Italy) and it was found that in the flasks stored with oxygen scavenger practically all oxygen was removed while in the flasks without oxygen scavenger the content of oxygen was 18%.

A lower content in hexanal in the samples containing the absorber sachet were observed. The samples containing oxygen scavenger presented, after three days, a 12.25% less of hexanal than the samples stored without the oxygen absorber. The test results are summarized in Table II. In a second series of trials the content of the sachets were also analysed by SPME/GC-FID. The content of the sachets were place into 20 mL headspace vials and they were hermetically capped with a silicone septum. The SPME and chromatographic conditions were the same as those specified for the hazelnuts samples analysis. Different components were found and among these hexanal was also detected. For that reason other assays were conducted to investigate the possible absorption of volatile compounds by the oxygen scavenger.

"[Insert

Two vials (120mL) with 10mL of a hexanal solution in water (500 mg kg -1 ) were prepared. In one of the vials, oxygen scavenger was suspended on the top of the container (not to be in contact with the liquid) and both vials were hermetically closed and stored at room temperature. After one week an SPME/GC-FID analysis of the headspace of the two vials were made.

As shown the figure 2, the hexanal content in the headspace of vials with the oxygen scavenger was considerably reduced comparing with the one without oxygen scavenger.

The oxygen scavenger sachet was opened and the powder contained in the sachet was analysed. The quantity of hexanal found in the powder cannot explain the differences found in the 120mL headspace vials and this could be due to the fact that probably it's difficult to extract again hexanal from the powder after the adsorption.

Briefly, although the oxygen scavengers shown to reduce the oxidation process, other volatile components among these hexanal were also absorbed. Since the hexanal is an indicator of the rancidity, this fact could mask the real state of the food product and

  years solid phase micro extraction (SPME) has been proven to be an alternative, promising and innovative technique that combines the simultaneous extraction and pre-concentration steps. It is simple, fast, uses little solvent, does not require sample preparation and is inexpensive.

  sachets based on iron powder and with capacities of 20 mL were used in the experiments.

  the instrument and confirmed by the correspondence of the retention time obtained with the analysis of pure standard.The software HP-Chem Station from Hewlett-Packard was used for data processing."[Insert TableI about here]"

Figure 1 .

 1 Figure legends

Figure 2 .

 2 Figure 2. -Chromatogram of hexanal content in headspace vial with and without oxygen scavenger

  Table II about here]"

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Anna M Balinova
email: abalinova@abv.bg

Rositsa I Mladenova

Deyana D Shtereva

pesticide residues in peaches intended for baby food

Keywords: pesticide residues, chlorpyrifos-methyl, fenitrothion, procymidone, 16 vinclozolin, peaches, processing, baby food 17

Effects of processing on pesticide residues in peaches intended for baby food

Anna Balinova, Rosica Mladenova, Deyana Shtereva

Introduction 2

The risk assessment of dietary intake of pesticides is important for ensuring safe food 3 production (Lentza-Rizos 2001). Special attention should be given to the health protection 4 of babies and small children, as they are the most vulnerable group of population 5 (Matsumura 2004[START_REF] Dencker | Susceptibility in utero and upon neonatal exposure[END_REF]. In order to protect the health of infants and small 6 children in the European Union (EU), very strict limit has been introduced by the 7 European Commission (EC) for any pesticide potentially occurring in baby food. Residues of pesticides in food are influenced by storage and processing that occurs 13 between harvesting of raw commodities and consumption of prepared foodstuffs (Holland 14 et al. 1994). Procedures used in food processing have been shown to have considerable 15 effects on residue levels [START_REF] Holland | Effects of storage and 23 processing on pesticide residues in plant products[END_REF], Scattenberg et al. 1996). In general 16 significant decrease in residues occurs (Scattenberg et al. 1996). However concentration 17 of residues in some food fractions has been occasionally observed [START_REF] Hajslova | Pesticides[END_REF]. The 18 extent and direction of the pesticide changes during processing depend on physico-19 chemical properties of the chemicals, type and conditions of the processes and nature of 20 the crops (Pappas et al. 2003[START_REF] Elkins | Effect of commercial processing on pesticide residues in selected 16 fruits and vegetables[END_REF]. The insecticides chlorpyrifos-methyl, fenitrothion and the fungicides procymidone, peaches. The EU MRLs established for peaches intended for general nutritional uses are 2 1 mg/kg for procymidone, 0.5 mg/kg for chlorpyrifos-methyl and fenitrothion and 0.05 2 mg/kg for vinclozolin (European Commission 2002). The existence of international 3 MRLs indicates that the corresponding pesticides are authorised to be used on particular 4 crops and that detectable residues of the order of magnitude of the MRL are left at 5 harvest. Pesticides with international MRLs of the order of 0.01 mg.kg -1 were not 6 included in the study with the exception of pesticides of high frequency of occurrence of 7 samples with residues exceeding MRLs (monitoring studies). to the problems of assurance the high quality of analytical methods both in respect of 1 quantitative parameters (sensitivity, trueness, precision, and range) and of qualitative 2 assessment (identification and confirmation). Implementation of analytical methods 3 capable of determining the pesticide residues at ultra-trace levels (at or below 0.01 mg.kg - 4 1 ) was mandatory in the study. Ehrenstorfer (Augsburg, Germany). Stock solutions (1.0 mg.ml -1 ) of each pesticide were 14 prepared in ethyl acetate and stored in a freezer. Working standard solutions at 15 concentration rates of 5 ng.ml -1 -500 ng.ml -1 were prepared by diluting of stock solutions 16 with ethyl acetate and stored at 4°C in dark. Double distilled water was used when needed 17 in experiments. Filter paper "blue spot 391", fine-pored, was obtained from Sartorius AG, 18 Goettingen, Germany. Capillary column AT™-5ms, (30 m × 0.25 mm × 0.25 µm) was obtained from Alltech 23 Associates, Inc. (Lokeren, Belgium). The purity of nitrogen used was greater than 99.999 24 % (SIAD, Bulgaria). Vacuum manifold (Varian Inc) was used for SPE. (fenitrothion 500 g.l -1 a.i.) and Ronilan (vinclozolin 500 g.kg -1 a.i.) were carried out in the 7 orchard of the experimental station near the town of Petrich on 10 September 2004. • Fruits, to be submitted to washing with tape water 1

• Fruits, to be submitted to mechanical peeling after washing 2 • Fruits, to be submitted to chemical peeling after washing 3 Approximately 3 kg of whole fruits were taken of each type. The stones were removed 4 from the fruit selected to be analysed without washing. The weights of the edible part and 5 of the stones were taken. The samples selected to be analysed after washing were 6 intensively washed with tap water and processed as described above. The washed fruits 7 were divided into two sub-samples and submitted to different types of peeling: 8 mechanical, typical for household processing and chemical, applied mostly in industrial 9 processing. The weights of the edible part of the fruits, stones and peels of mechanically 10 peeled fruits were taken. The peel of mechanically peeled fruit were weight separately. polypropylene cartridges manually packed with 400 mg ENVI-Carb, conditioned with 10 12 ml ethyl acetate: methanol (8:2) followed by 5 ml methanol and washed with 10 ml water.

13

The sorbent was never allowed to dry during the conditioning and sample loading steps.

14

The samples were forced to pass through the sorbent under vacuum at rate of 10 ml.min -1 .

15

After the passage of the sample, the sorbent was washed with 0.4 ml methanol and dried 16 under vacuum for 30 min. The pesticides were eluted with 6 ml ethyl acetate-methanol 17 (8:2) at rate of 1 ml/min and collected in 10 ml graduated tubes. The eluates were 18 submitted to the second clean-up step by using SAX-PSA Bond Elut cartridges. The 19 sorbent was washed with 2 ml methanol and conditioned with 2 ml ethyl acetate-methanol 20 (8:2). The samples were passed through the cartridge at rate of approximately 1 ml.min -1 .

21

After the passage of the sample, the elution of the analytes was completed by washing 22 twice with 1 ml ethyl acetate-methanol (8:2). Combined eluates were collected in 10 ml (unpeeled fruits, peels) were diluted to bring them within the calibrated range. Samples 1 containing low-level residues (peeled fruits, puree of peeled fruits) were concentrated to 2 bring the residue levels at or over the lowest calibrated level.

3 Chromatographic conditions. GC-ECD operating conditions: carrier gas nitrogen, at flow 4 rate 2.5 ml.min -1 ; make up nitrogen 30 ml.min -1 ; injector temperature 270°C, splitless Processing studies. Peeling, juicing and thermal processing are identified as processing 4 procedures deserving attention with respect to their effect on pesticide residues (Holland 5 et al. 1994[START_REF] Hajslova | Pesticides[END_REF], WHO Guidelines for predicting dietary intake of pesticide 6 residues 1997). The effect of each of these processes on residues in peach puree is 7 dependent on the physico-chemical properties of the pesticides applied, on their 8 mechanism of action, processing conditions etc. The residue concentrations of the 3 show that the cold water washing is a procedure that has limited effectiveness in 3 reduction of residues and the reduction does not correlate with solubility and polarity of 4 the compounds. This was also observed by Krol et al. (2000). Mechanical peeling, typical 5 for household processing and chemical peeling, applied mostly in industrial processing, 6 are the procedures which make a substantial contribution to reduction of residue levels in 7 the fruit flesh. The bulk of the residues are removed with the peel. Residues of systemic 8 pesticides penetrate into the plant tissues. Comparatively less of the systemic pesticide 9 residues are therefore removed with the peel. The relatively higher value of P 2 calculated 10 after mechanical peeling (table 3) for the systemic fungicide procymidone, compared to 11 the other non-systemic compounds supports this concept. Chemical peeling results in the 12 same relative efficiency in residue reduction. 13 14 Thermal processing (cooking, sterilisation) may have highly variable effects depending on 15 conditions (time, temperature, degree of moisture loss, whether the system is opened or 16 closed) [START_REF] Holland | Effects of storage and 23 processing on pesticide residues in plant products[END_REF] and on the properties of the compounds. Under the conditions of 17 the boiling process, loss of the phosphorous compounds chlorpyrifos-methyl and 18 fenitrothion occurred. Despite the loss of moisture the residue concentrations of both 19 pesticides in concentrated puree were reduced significantly (P 4 values calculated for the 20 step of concentration were 0.8 and 0.6 respectively). The effect of cooking temperature 21 was the main reason for accelerating the loss of organophosphates, as these compounds The process of sterilisation in hermetically closed jars did not further influence the residue 6 levels of the pesticides studied. The reduction of residue concentrations resulting from the 7 whole processing procedure of peeled fruits, calculated as final P value is significant, 8 especially for chlorpyrifos-methyl and fenitrothion. The reduction of residues of these 9 compounds in the final products was of the order of more than a hundred-fold (table 2). 10

The residues of procymidone and vinclozolin in the final products obtained through the 11 processing of peeled fruit were reduced about ten times. [START_REF] Dencker | Susceptibility in utero and upon neonatal exposure[END_REF], National Research Council 1993). [START_REF]Commission Directive 2002/63/EC[END_REF] The EC Directives on infant formulas and baby foods state that these products shall not that the processed foods based on peaches treated with procymidone and vinclozolin are 13 not suitable for feeding to infants and small children. The residues of chlorpyrifos-methyl and fenitrothion are significantly reduced during the 16 pureeing process. They are suitable for treatment of peaches, intended for production of 17 baby food. Peeling of fruits is recommend in all cases where the final product is intended 18 for baby food.

8

  Directives 2003/13/EC and 2003/14/EC established a general maximum residue limit (EU 9 MRL) of 0.01 mg.kg -1 for any individual pesticide in processed cereal-based foods and 10 baby foods (European Commission 2003 a, b).11 12

  23vinclozolin were selected to be included in the study taking into consideration the 24 statistical evaluation of the quantities applied in practice and especially their use on 25

  the very stringent Directive on residues in baby food makes it 10 necessary to understand the behaviour of pesticides during processing. Optimisation of all 11 technological parameters would allow final products to be prepared in compliance with 12 baby food safety requirements after processing of potentially contaminated raw materials. 13 14 The aim of this work was firstly to study the effect of fruit processing procedures on 15 behaviour of chlorpyrifos-methyl, fenitrothion, procymidone and vinclozolin residues in 16 peaches intended for production of baby food puree. Secondly, the aim was to establish 17 the processing factors for intermediate and final products of simulated industrial and 18 household processing of peaches, treated with the selected pesticides. Thirdly we aimed 19 to contribute to refinement of the plant protection technologies and processing 20 technologies in order to guarantee production of baby food in compliance with

  13

19 20 A

 20 Hewlett-Packard gas chromatograph Model 5890 Series II equipped with 63 Ni electron 21 capture detector (ECD) was used. Split-splitless injector operated in the splitless mode.

22

 22

  25

  sampling. The field treatments of peach trees cultivar Fayette with 2 the commercial formulations Reldan 50 EC (chlorpyrifos-methyl 500 g.l -1 active 3 ingredient (a.i.) and Sumilex 50 WP (procymidone 500 g.kg -1 a.i.) were carried out in the 4 orchard belonging to the experimental station on peaches near the town of Sliven on 22 5 August 2003. The field treatments with the commercial formulations Аgria 1050 6

•

  applied at the recommended rate of 0.15% a.i. by using common 10 orchard spraying equipment. Each pesticide working solution was applied on four trees 11 and three trees received no treatment (control trees). Samples were collected 3 days after 12 treatment. The aim was to obtain fruits containing incurred residues at concentration high 13 enough to be traced in all intermediate products and in the final products of the simulated 14 industrial processing to baby food puree. 40 kg of peaches were collected of each variant 15 of treatment and of the untreated control trees. The sampling was carried out according to 16 the recommendations of the EC for residue analysis sampling (All processes applied to the study for processing effects 20 assessment were planned in a way to correspond as closely as possible to those that occur 21 in actual practice. The field samples of each pesticide/peach combination were put into 22 polyethylene bags and immediately transported to the laboratory. The following sets of 23 samples of each type were prepared for processing and pesticide residues analysis: 24

11

  The edible parts of the fruit were blended and stored in plastic bags in a freezer at (-23 o C) 12 for simulated industrial processing and analyses. 13 14 The processing procedures were carried out under the following conditions: washing with 15 tap water at 16 0 C ± 2 0 C; chemical peeling with 4% NaOH solution at 90 0 C, then after 16 removing the peel -2% citric acid solution and washing with water; concentration by 17 boiling under open conditions at 90 0 C ± 2 0 to 24% ± 1.7% dry content; thermal 18 sterilisation in closed jars at 90 0 C ± 2 0 for 25 min.

  step of the processing procedure samples were taken and submitted to 21 residue analysis. All procedure steps and corresponding samples taken for analysis were[START_REF] Holland | Effects of storage and 23 processing on pesticide residues in plant products[END_REF] given consecutive numbers as presented in figure1.

  Analytical samples (10 g) of the thoroughly homogenised material were 3 weighed and taken at the selected steps of the processing procedure. Acetone (20 ml) was 4 added and samples were extracted by mechanical shaking for 30 min. Extracts were 5 filtered, residues washed by shaking with 2 x 20 ml acetone, and filtrates combined and 6 homogenised. A half of the volume of each mixed filtrate was taken for further SPE 7 clean-up and pre-concentration. 8 Sample clean-up. The aliquots of the acetone extracts (approximately 25 ml) were diluted 9 with doubly-distilled water (200 ml) and the diluted extracts were submitted to two step 10 SPE clean-up/preconcentration. The first step of SPE was carried out by using 11

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  23graduated tubes. The initial volumes of the samples were adjusted at 5 ml (1g matrix.ml -1 ) 24 by evaporation under gentle stream of nitrogen. Samples containing high-level residues 25

5 time 1

 51 .5 min; detector temperature 300°C. Oven temperature program: 100°C, hold 1 min; 6 rate 20°C/min to 260°C final temperature, hold 3 min. Injection volume was 1 µl for all 7 samples. Quantification was performed by using external standards. Matrix-matched 8 calibration standards were used for all quantifications. 9 Preparation of matrix-matched calibration standards. Blank extracts of each type of 10 samples were submitted to SPE clean up as described above. Series of standard solutions 11 were prepared by adding 0.1 ml of pesticide standards of desired concentration to cleaned 12 extracts aliquot to 5g blank matrix and the volumes were adjusted to 5 ml. In cases when 13 final sample extracts were diluted or concentrated the matrix extracts in calibration 14 standards were adjusted in order to ensure similar matrix concentration in sample validated for peaches. The linearity of ECD response was determined in 20 the range of 0.005 ng -0.05 ng. The correlation coefficients r 2 of the four pesticides 21 studied were higher than 0.98 (five-point calibration curve). Concentrations of the 22analytes in the samples were calculated by using single-level calibration method. This 23 approach is recommended in case the detector response is variable with time (Document 24SANCO/10476/2003). In our studies it was confirmed that single-level calibration gave 25

22 23Page

 22 The key factors for the effectiveness of washing in reduction of residue concentration are 24 the age of the residues and the mode of action (systemic or non-systemic). Sampling was 25 after treatment in order to obtain residues incurred into cuticular waxes 1 or deeper for closely simulating the processes in actual practice. The results presented in 2 table

  resulted in a substantial increase of procymidone and 1 vinclozolin residues (P 4 values calculated for the step of concentration were 2.3 and 4.5 2 respectively). Procymidone, derivative of dicarboximide and vinclozolin, an oxazolidine 3 derivative, are characterised by relatively high thermal stability(Tomlin 2000).

  fruit is substantially less effective in reducing the residue levels in 14 final products. While the residues of organophosphates still undergo reductions of 2.5 to 5 15 times, vinclozolin residue levels in peach puree produced from unpeeled fruit does not 16 change. The systemic fungicide procymidone is concentrated under this processing 17 procedure (P final.(unpeeled fruit) is 1.3). 18 19 All EC Directives concerning baby food safety stipulate that the exposure of infants and 20 children to food contaminants is of particular concern because of their possible increased 21 susceptibility for adverse effects. Growing and developing organisms have particular 22 sensitivity to toxic compounds

  , detectable residues of the order of magnitude of the MRL may be 4 present in the particular crop at harvest. Procymidone residues of the order of magnitude 5 of 2 mg/kg could be expected in individual peach fruit. A compliance with the safety 6 requirements for general population of processed product (peach puree) may be expected 7 only in case when peeling procedure was carried out of the fruits treated with 8 procymidone. The same is valid for peaches treated with vinclozolin. Processing 9 procedures for pureeing are not effective enough to reduce the residues in the final 10 product to levels at/below the general MRL of 0.01 mg.kg -1 established by the EC for any 11 individual pesticides in processed baby food. The results of the presented work indicate 12

Figure 1 .

 1 Figure 1.

Figure 2 .

 2 Figure 2. Chromatograms of mixed standard solution (A) at concentration 0.1 µg/ml,

Table 1 .

 1 Recoveries and standard deviations of fortified pesticides from peaches versus

	19

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Table 2 .

 2 Residues at crucial steps of simulated industrial processing of peaches treated with pesticides (mean of 2 samples)

	Mean residues, mg/kg

Table 3 .

 3 Processing factors of intermediate and final products of peach-based baby food puree Processing factors are calculated as ratio between the residues (R) in samples, taken at consecutive steps of processing shown in figure1: P 1 =R (2) / R (1) P 2 = R (6) / R (2)

	Step		Processing Factors (P)*
		Chlorpyrifos-	Fenitrothion Procymidone Vinclozolin
		methyl
	P 1 -Washing	0.8	0.6	0.5
	P 2 -Mechanical peeling	0.02	0.05	0.2	0.09
	P 3 -Chemical peeling	0.01	0.06	0.06	0.02
	P 4 -Concentration	0.8	0.6	2,3	4.5
	P 5 -Sterilization	1.0	1.0	1.0	0.9
	P final (chemical peeling)	0.007	0.002	0.1	0.1
	P final (unpeeled fruit)	0.2	0.4	1.3	1.0

*

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Acknowledgement

21

The financial support of NATO Program "Science for Peace" is highly acknowledged.


Jens Hinge Andersen

Rikke L Lindeberg Bille

Kit Granby

Rikke L L Bille

determinations of glyphosate, chlormequat and mepiquat residues in wheat

HAL is

Introduction

Glyphosate is a widely used herbicide that is employed in weed control after sowing and before the harvest of different kinds of crops like cereals, peas and beans. Glyphosate is a systemic herbicide that is absorbed through the leaves of the weed and distributed in the plant. Glyphosate is the most frequently used pesticide in Denmark (Danish EPA 2004). Chlormequat and mepiquat are both plant growth regulators. Chlormequat is by far the most widely used plant growth regulator in Denmark (Danish EPA 2004) accounting for 85% of the total use of plant growth regulators in 2004. Both chlormequat and mepiquat are used on cereals, reducing the growth of the lowest part of the straw and thereby making it stronger. All three pesticides are sold and used as a salt of the compounds. Glyphosate is mostly sold as an ammonium salt and chlormequat and mepiquat as chloride salts.

Chlormequat is the most frequently found pesticide in the Danish monitoring of pesticide residues in cereals. In 1997, 83% of 46 cereal samples contained chlormequat (mean of all samples: 0.32 mg/kg) and in 1999 87% of 52 samples contained chlormequat (mean of all samples: 0.23 mg/kg) [START_REF] Granby | Investigation of the herbicide glyphosate and the plant growth regulators chlormequat and mepiquat in cereals produced in Denmark[END_REF]. In 2003, (Danish VFA 2004) and 2004(DFVF 2006) the frequency decreased to 25% (of 124 samples) and 20% (of 161 samples), respectively. The frequency of glyphosate residues in cereals had decreased through the period 1998-2001 from >50% in 1998-1999 to <20% in 2000-2001. No residues of glyphosate were found in the 124 and 161 cereal samples analysed for glyphosate in the Danish pesticide monitoring program in 2003and 2004, respectively (Danish VFA 2004, DFVF 2006). The decrease in glyphosate findings is at least partly due to statements from the Danish trade organizations for agriculture and bakeries, that they would produce bread without glyphosate for the consumers. The frequent use of glyphosate and chlormequat and the residues found in cereal samples makes it even more important to have reliable analytical results, and hence increase the need for intercomparison studies. food. HPLC with different detectors e.g. conductivity detector [START_REF] Fegert | Determination of mepiquatchloride in animal and plant matrices by ion chromatography with conductivity detection[END_REF], fluorescence detector [START_REF] Hogendoorn | Rapid determination of glyphosate in cereal samples by means of pre-column derivatisation with 9-fluorenylmethyl chloroformate and coupled-column liquid chromatography with fluorescence detection[END_REF] and MS/MS detection [START_REF] Juhler | Residues of Chlormequat and Mepiquat in Grain -Results from the Danish National Pesticide Survey[END_REF][START_REF] Granby | Analysis of glyphosate residues in cereals using liquid chromatography-mass spectrometry (LC-MS/MS)[END_REF][START_REF] Riediker | Determination of chlormequat and mepiquat in pear, tomato, and wheat flour using on-line solid-phase extraction (Prospekt) coupled with liquid chromatography-electrospray ionization tandem mass spectrometry[END_REF] are most common, but also other methods like GC with pulsed flame photometric detection [START_REF] Tseng | Simultaneous Quantification of Glyphosate, Glufosinate, and Their Major Metabolites in Rice and Soybean Sprouts by Gas Chromatography with Pulsed Flame Photometric Detector[END_REF]) and nitrogen-phosphorous detection [START_REF] Roy | Method for the determination of residues of the herbicide glyphosate and its principal metabolite, aminomethylphosphonic acid, in plant materials by nitrogen-selective gas chromatography[END_REF] as well as electrophoresis with ultra violet detection [START_REF] Galceran | Separation of quaternary ammonium herbicides by capillary electrophoresis with indirect UV detection[END_REF]) have been used to determine these residues.

Glyphosate, chlormequat and mepiquat have been part of pesticide monitoring programmes in some European countries for several years (European Commission 2004, European Commission 2003, European Commission 2002). To maintain accreditation for the analytical methods, laboratories have to undertake in-house validation of analytical methods. One part of this is participation in intercomparison studies (ISO/IEC 17025 2000). Very few intercomparison studies on glyphosate, chlormequat and mepiquat in cereals have been published, and organizations which offer proficiency testing e.g. FAPAS  have not been offering these compounds in their programme. CEN organised an intercomparison study in 2001 on the determination of chlormequat and mepiguat in different non-fatty matrices including wheat flour, using LC/MS/MS. The outcome of the intercomparisons was a standard which is still under development (prEN 15054/15055). Because of the few intercomparisons offered an intercalibration of glyphosate, chlormequat and mepiquat in wheat was organised by The Danish Institute for Food and Veterinary Research.

Organization of the ring test

Preparation of the materials

Three samples and a blind sample were prepared from wheat. From each sample, thirty-five subsamples with 50-55 g were prepared in polypropylene bags, marked and stored at -18°C until dispatch on 18th of January 2005.

Blind sample. Kernels of organically grown wheat, bought from a domestic retailer, were used as blind sample material. The material was milled in a centrifugal mill (Retch Ultra ZM1000) with a 0.5 mm sieve to produce the final blind sample (sample C). chlormequat, mepiquat and glyphosate, respectively, was prepared in water. 3.60 ml of the solution were added dropwise to 250 g of kernels from the blind sample material while slowly agitating the sample material in a polyethylene container. After mixing, the fortified portion was kept overnight in a dessicator to remove excess of water. The portion was mixed with an additional 1750 g of kernels from the blind sample material by thoroughly agitating the sample in a polyethylene bag, and the mixture was milled in the centrifugal mill with a 0.5 mm sieve. This sample was labelled sample A when sent to the participants.

Sub-samples of domestic and foreign samples of wheat kernels from a residue-monitoring project were selected, based on measurements of their content of chlormequat. The residue-monitoring project was undertaken by a contract laboratory. Neither glyphosate nor mepiquat had been detected in the sub-samples (quantification limits for the survey: glyphosate: 0.1 mg/kg; mepiquat: 0.01 mg/kg). Kernels from seven samples with measured contents from 0.5 to 1.4 mg/kg (approx. 1500 g) were mixed with 500 g of kernels from the blind sample material and milled in the centrifugal mill with a 0.5 mm sieve. When sent to the participants, this sample was labelled sample B.

Sub-samples of domestic and foreign wheat kernel samples from a residue-monitoring project were selected, based on measurements of their content of glyphosate. Some of the sub-samples also contained chlormequat. Mepiquat had not been detected in the sub-samples. Kernels from nine samples (with 0.08 -0.9 mg/kg glyphosate) were combined (approx. 2000 g). Chlormequat had been found in three of the samples (0.16 -0.6 mg/kg). The sub-samples were mixed and milled in the centrifugal mill with a 0.5 mm sieve and sent to the participants as sample D.

Homogeneity and stability

Homogeneity and stability tests were done on all samples except for the blind sample. The analytical methods used (Granby et al. 2003, Juhler and[START_REF] Juhler | Residues of Chlormequat and Mepiquat in Grain -Results from the Danish National Pesticide Survey[END_REF] have been developed and validated at the Danish Institute for Food and Veterinary Research.

Method of analysis for glyphosate.

The homogenised sample (3 g) was extracted twice with 25 ml MilliQ water by ultrasonication.

After centrifugation and filtration, glyphosate was cleaned up online on a polystyrene based reverse

Method of analysis for chlormequat and mepiquat.

The homogenised sample (10 g) was extracted with methanol/water/acetic acid by Ultra-Turrax.

The centrifuged extracts were cleaned on a SPE-C 18 column with methanol/water/ ammonium acetate buffer. Chlormequat and mepiquat were quantified by LC-MS/MS using a reversed phase HLPC column and positive electrospray. 13 C labelled chlormequat (MW=125) was used as internal standard. Fragmentation for chlormequat: m/z 122 58, for 13 C -chlormequat: m/z 125 61. Fragmentation for mepiquat: m/z 114 98.

Homogeneity test. The samples A, B and D were tested for homogeneity before dispatch to the participants. From each sample, six subsamples were randomly chosen: Two subsamples from the first ten subsamples, two from the middle fifteen and two from the last ten subsamples. Each of these subsamples were analysed in duplicate before being dispatched to the participants. No differences between sub-samples were found, when testing the single measurements by one-way Analysis of Variance (ANOVA) [START_REF] Miller | Statistics for Analytical Chemistry[END_REF]) at 5% significance level, see table I.

Insert Table I Stability test. After the date that was set as the last reporting date, three sub-samples from each sample were randomly chosen: One sub-sample from the first ten sub-samples, one from the middle fifteen and one from the last ten sub-samples. Each sub-sample was analysed in duplicate.

Insert Table II

As seen in table II, no differences between sub-samples were found when testing the single measurements by ANOVA at 5% significance level, confirming the homogeneity of the subsamples. No differences between the average from the homogeneity test and the average from the Note that the sub-samples for the homogeneity test and the stability test are not the same. The relative differences therefore include variation between sub-samples.

Sample dispatch and data return

Six European laboratories participated in the test. The laboratories were allowed to use their own method for the analysis. The participants were asked to analyse each sample in duplicate and report the results on the spreadsheet dispatched with the samples. They were also asked to send information about quantification limits and recovery check. Analysis and reporting of the blank sample were optional. Finally information on the analytical principle applied was also requested.

The test materials were frozen and sent by mail to the laboratories on 18th of January 2005. Results were reported to the organiser no later than 18th of February 2005.

Statistical treatment

To preserve anonymity each laboratory was assigned a code which was known only to the laboratory and the organizer. The mean and standard deviation were calculated for each data set.

All the results were tested using Grubb's test to see if any outliers or stragglers could be found.

When using Grubb's test the within-laboratory variation is assumed to be equal. To test this, Cohran's test (ISO/EIC 5725-2 1995) was used. No outliers or stragglers were found. This could be due to the very small data set.

Correlation plots

Correlation plot. To check if the methods of analysis used in the different laboratories performed equally, correlations plot for each compound was done for the results from each laboratory. A strong correlation between the pair of results from each laboratory indicates a systematic component [START_REF] Youden | Statistical Techniques for Collaborative Tests[END_REF].

Results

All results from the participating laboratories were received before the deadline (18th of February 2005). Five of the participants analysed the blind sample (C). No residues were reported.

Analytical methods employed

Several different method principles were used for the analysis of glyphosate: GC/MS, HPLCfluorescence and LC/MS/MS. Five of the laboratories used LC/MS/MS methods for chlormequat and mepiquat analysis. One laboratory used LC-MS

Received results and correlation plot

Glyphosate. Results for glyphosate are listed in table IV.

Insert table IV

For sample A, two laboratories (2 and 4) had results that seem somewhat lower than the fortified level. Of these two, laboratory 4 reported a low recovery for their control sample (34%). The remaining four laboratories deviated less than 25% from the fortified level. Recoveries for all laboratories can be seen in table IV.

For sample B, glyphosate were detected by three laboratories (1, 3 and 6) at levels that were generally lower than the limit of quantification (LOQ) for the remaining laboratories. Thus the absence of detection by these laboratories could be in agreement with the low concentrations found by the other laboratories. Table VIII shows the LOQ's for all participating laboratories.

For sample D, five laboratories detected glyphosate. Three laboratories (1, 3 and 6) reported levels at 0.20-0.25 mg/kg while laboratory 2 and 4 reported levels at 0.07-0.09 mg/kg. The withinlaboratory variation calculates to 14%, 5% and 12% for sample A, B and D, respectively. The between-laboratory precision (ISO/EIC 43 1997) is calculated to 39% and 48% for sample A and D, which is high compared to the Horwitz precision [START_REF] Horwitz | Evaluation of analytical methods used for regulation of foods and drugs[END_REF]) (17% at 0.8 mg/kg, 20% at 0.2 mg/kg). Insert figure 1 The strong correlation (figure 1) between results from sample A and D (r 2 =0.95) indicates that the between-laboratory variation has a highly systematic component. It seems like the participating laboratories are divided in two groups: one with laboratories 1, 3 and 6 having high results and one with laboratories 2 and 4 having low results. Laboratory 5 falls in the group with high results for sample A, but did not detect any glyphosate in sample B and D. This could be due to fact that laboratory 5 has the highest LOQ for glyphosate of all the participating laboratories.

For glyphosate, there is a very high variation between the results obtained by the different laboratories, indicating a need for improvement of the quality assurance and/or optimisation of the method of analysis used for glyphosate.

Insert table V

When considering the systematic differences in relation to the different analytical techniques used (see table V) by the participating laboratories there is no clear trend. All laboratories used aqueous solutions for extraction, five of them used pure water and one laboratory used a borate buffer at pH 9. Laboratory 5 and 6 extracted the cereals twice with water while for the other laboratories the extraction procedure is not mentioned. Validation of the extraction efficiency of the method used by laboratory 5 and 6 on spiked samples had shown [START_REF] Granby | Analysis of glyphosate residues in cereals using liquid chromatography-mass spectrometry (LC-MS/MS)[END_REF]) that only 50-80% of the glyphosate was extracted during the first extraction, perhaps due to some kind of sorption of the glyphosate in a sort of equilibrium to the cereal flour. Hence insufficient extraction of glyphosate from the cereal flour may be a possible explanation for systematic low glyphosate results. The extraction study also showed that the extraction efficiency was not influenced by pH, e.g. extraction with an aqueous solution at pH 9 or at pH 2 did not differ from extraction with pure water. The clean-up techniques used by the participating laboratories were different e.g. ion-exchange (laboratory 1 and 2), reverse phase (laboratories 3, 5 and 6) and liquid-liquid partitioning (laboratory 4). Laboratory 1 used GC/MS detection after derivatisation, laboratory 2 used HPLC fluorescence detection, while laboratory 3-6 all used LC/MS/MS. VII). The analytical procedures did not differ much. The extraction solvents used were methanol-water with or without addition of acetic acid. Laboratory 1-4 did not use any clean up while laboratory 5 and 6 used reverse phase clean up. The laboratory having somewhat higher results for chlormequat and mepiquat, compared to the other laboratories, was laboratory 5 and 2, respectively.

Insert table VII

Limit of quantification

The reported LOQ from the laboratories are given in table VIII.

Insert table VIII

Most calculated recoveries were in agreement with the recoveries reported by the participants in tables 4 and 7; in particular, the low reported recovery on glyphosate by laboratory 4 (34%) is in good agreement with the calculated recovery (29%). For laboratory 2, the calculated recovery for glyphosate (49%) was lower than the reported recovery (92%) and for mepiquat the calculated recovery (241%) were higher that the reported (100%). Also the calculated recoveries from laboratory 5 for chlormequat (173%) and mepiquat (138%) are somewhat higher that the reported recoveries (109% and 93%, respectively).

Conclusion

In general, good within-laboratory precision was seen for all compounds tested. However, the between-laboratory precision was higher than expected by the Horwitz estimation [START_REF] Horwitz | Evaluation of analytical methods used for regulation of foods and drugs[END_REF].

This could be due to the small data set, resulting in outliers not being pointed out or it could be caused by systematic differences between results from the different laboratories. The combination of a high total variation and relatively few participants makes a calculation of Z-scores meaningless.

For glyphosate and chlormequat, the strong correlation of results from different samples indicates that the between-laboratory variation has a systematic component. It was not possible to correlate differences in the results between the laboratories to the use of different methods of analysis.

  separated by ion chromatography-HPLC. Sodium ions were removed from the eluent by automatic ion suppression before quantification by MS/MS (negative electrospray). 2-13 C 15 N-glyphosate was used as internal standard. Fragmentation for glyphosate: m/z 168 150. For the internal standard 2-13 C 15 N-glyphosate: m/z 170 152.

  LC/MS (see table

Fig. 1

 1 Fig.1Correlation between glyphosate results for sample A and D. Each point represents the pair of results from one laboratory. (Laboratory 5 has been excluded as the result for sample D was below LOQ). A line has been drawn through origin and the center of gravity for the population (the mean for each sample).

Fig. 2

 2 Fig. 2 a) Correlation between chlormequat results for sample A and B. b) Correlation between chlormequat results for sample A and D. Each point represents the pair of results from one laboratory. A line has been drawn through origin and the center of gravity for the population (the mean for each sample).

Table I

 I Homogeneity test. Differences between the means of the subsamples were tested by one-way ANOVA. Each of the six subsamples were analysed in duplicate.

	Added (mg/kg) Average (mg/kg, n=6)	Recovery (%)	SD * (mg/kg)	CV † (%)	P ‡ (%)
	Sample A
	Glyphosate	0.800	0.715	89	0.057	8	68
	Chlormequat	0.377	0.356	94	0.016	5	64
	Mepiquat	0.384	0.380	99	0.027	7	8
	Sample B
	Glyphosate		0.063		0.078	12	39
	Chlormequat		0.254		0.021	8	41
	Mepiquat		0.001 ¶		0.002	-	-
	Sample D
	Glyphosate		0.218		0.008	4	79
	Chlormequat		0.170		0.011	7	52
	Mepiquat		0.001 ¶		0.001	-	-
	* Standard deviation
	† Coefficient of variation
	‡ No significant difference between subsamples where P>5%
	¶ Below quantification limit (0.01 mg/kg)

Table II

 II Homogeneity in the stability test. Differences between the mean of the subsamples tested by one-way ANOVA. Each of the three subsamples were analysed in duplicate. Table III Stability test. Difference between the measured contents before and after the test period tested by one-way ANOVA. See Table 1 and Table 2 for details.Table IV Reported results for glyphosate. Sample A was fortified with 0.800 mg/kg.

		Food Additives and Contaminants	Page 16 of 20
	Added (mg/kg) Average (mg/kg, n=3) 0.800 0.769 0.377 0.349 0.384 0.346 0.060 0.248 0.001 ¶ 0.225 0.184 0.001 ¶ ‡ No significant difference between subsamples where P>5% Sample A Glyphosate Chlormequat Mepiquat Sample B Glyphosate Chlormequat Mepiquat Glyphosate Chlormequat Mepiquat * Standard deviation ¶ Below quantification limit (0.01 mg/kg) † Coefficient of variation Sample D F o r P e e r Recovery (%) 96 93 90 e SD * (mg/kg) 0.034 0.024 0.019 0.008 0.007 0.002 0.011 0.012 0.001 w i v R e Laboratory no. X1 (mg/kg) X2 (mg/kg) Average (mg/kg) Reported recovery (%) Sample A 1 0.81 0.702 0.756 77 2 0.382 0.402 0.392 92 3 0.574 0.661 0.62 96 4 0.21 0.25 0.23 34 5 0.69 0.77 0.73 113 6 0.995 0.75 0.873 112 Sample B 1 0.022 0.018 0.02 77 2 <0.1 <0.1 <0.1 -3 0.024 0.025 0.024 103 4 <0.05 <0.05 <0.05 34 5 <0.15 <0.15 <0.05 113 6 0.07 0.071 0.071 112 Sample D 1 0.226 0.186 0.206 77 2 0.066 0.106 0.086 92 3 0.189 0.202 0.20 96 4 0.076 0.068 0.072 34 5 <0.15 <0.15 <0.15 113 6 0.246 0.254 0.25 112 F o r P e e r R e v i e w CV † (%) P ‡ (%) 4 74 7 10 5 9 13 54 3 21 --5 58 7 11 --	O n l y
	Sample A Glyphosate Chlormequat Mepiquat	Relative difference * (%) 7.6 -1.9 -9.0	P † (%) O n l 18 63 9 y
	Sample B
	Glyphosate	-5.1	57
	Chlormequat	-2.2	66
	Mepiquat	- ‡	-
	Sample D
	Glyphosate	3.2	32
	Chlormequat	8.2	13
	Mepiquat	- ‡	-

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Table V

 V Method information for analysis of glyphosateTable VIReported results for chlormequat and mepiquat. Sample A was fortified with 0.3765 mg/kg and 0.3835 mg/kg of chlormequat and mepiquat, respectively.

				Sample			No. of
	Laboratory no.	amount (g)	Extraction Solvent	extraction		Clean up	Detection principles	Internal standard
	1			4		Water		-*	Dichloromethane, Chelex 100 and AG1X8 anion exchange	GC-MS after derivatization with TFAA and HFB	AEPA
	2			30		Water		-*		Ion-exchange	HPLC-Fluorescence	-*
	3			5		Water		-*		Envi-carb	LC-MS/MS	Glyphosate C13/N15
	4 5			5 3	Water+borate buffer (pH 9) Water Chlormequat	-* 2		Liquid-liquid partition Polystyrene-based RP-column (online) Mepiquat	LC-MS/MS ESI LC-MS/MS ESI negative mode	None 13C15N-glyphosate
	6			3		Water		2		Polystyrene-based RP-column (online)	LC-MS/MS ESI negative mode	13 C 15 N-glyphosate
	Laboratory no. X1 (mg/kg) X2 (mg/kg) Average (mg/kg) Reported recovery (%) X1 (mg/kg) X2 (mg/kg) Average (mg/kg) Reported recovery (%)
	Sample A
	1	0.236		0.274	0.255		103		0.342	0.317	0.33	106
	2	0.406		0.372	0.389		106		0.962	0.887	0.924	100
	3 4 5 6 Sample B 1 2 3	0.378 0.41 0.67 0.401 0.18 0.277 0.248	0.364 0.41 0.63 F 0.398 0.196 o 0.284 r 0.37 0.41 0.65 0.34 0.188 0.28 0.254 0.25		83 96 109 109 103 106 83		0.26 n.a. * 0.45 0.382 -0.0044 † <0.01	0.322 n.a. 0.61 0.489 -0.0046 † <0.01	0.29 -0.53 0.436 <0.05 0.0045 † <0.01	82 -99 93 106 100 82
	4 5 6 Sample D 1 2	0.29 0.44 0.232 0.14 0.214		0.28 0.47 0.285 0.159 0.218	0.29 0.45 0.259 P 0.15 e 0.216	96 109 109 103 106		n.a. <0.01 <0.01 -<0.005	n.a. <0.01 <0.01 -<0.005	-<0.01 <0.01 <0.05 <0.005	-99 93 106 -
	3 4 5 6	0.177 0.23 0.30 0.142		0.158 0.23 0.29 0.166	0.17 0.23 0.30 0.154	83 96 109 r e 109		<0.01 n.a. <0.01 <0.01	<0.01 n.a. <0.01 <0.01	<0.01 -<0.01 <0.01	82 -99 93
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* Not analysed † The laboratory reported this result as below Limit of Quantification (0.005 mg/kg) Page 18 of 20 http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk Food Additives and Contaminants F o r P e e r R e v i e w O n l y

Table VII

 VII Method information for analysis of chlormequat and mepiquatTable VIII Reported Limit of Quantification (LOQ) and calculated recovery based on the results from spiked sample A.

	Laboratory no. Sample amount (g)	Extraction Solvent	No. of extraction	Clean up	Detection principles	Internal standard(s)
	1	20		Water/methanol		-*		None	LC-MS	-*
	2	10		Water/methanol		-*		None	LC-MS/MS	-*
	3	5	Water/methanol (75/25)		-*		None	LC-MS/MS	Chlormequat-D4, chlormequat-D3
	4 5	10 10 Glyphosate	Water/methanol (20:40) Water/methanol/acetic acid (75:24:1) Chlormequat	-* 1	None Bond Elut 500 mg SPE C18 Mepiquat	LC-MS/MS ESI LC-MS/MS ESI positive mode	None 13C-Chlormequat
	6	10	Water/methanol/acetic acid (75:24:1)	1	Bond Elut 500 mg SPE C18	LC-MS/MS ESI positive mode	13 C-Chlormequat
	Laboratory no.	LOQ (mg/kg) Recovery (%)	LOQ (mg/kg) Recovery (%)	LOQ (mg/kg) Recovery (%)
	1	0.01	95	0.02	68		0.05	86
	2	0.1	49	0.005	103		0.005	241
	3 4 5 6	0.01 0.05 0.15 F r 77 29 91 o 0.03 109	0.01 0.01 0.01 0.01	99 109 173 106		0.01 n.a. * 0.01 0.01	76 -138 114
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http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.ukFood Additives and Contaminants

Chlormequat. Results for chlormequat are listed in table VI.

Insert table VI

For sample A, four laboratories reported results that deviated less that 25% from the fortification level. All laboratories reported results between 0.20 and 0.45 mg/kg for sample B. Laboratory 5 reported the highest level of chlormequat in all three samples, significantly higher than the remaining laboratories. Laboratory 5 was asked if this could be due to reporting of the results as chlormequat chloride instead of the chlormequat cation, as this would move their results to the same range as the remaining laboratories. This was not the case and it has not been possible to find the reason for the higher results.

For sample D, all laboratories reported results between 0.15 and 0.30 mg/kg. The within-laboratory variation calculates to 5-6% for all the samples. The between-laboratory precision is 28-31% for all the samples, which is somewhat higher than the Horwitz precision (18-20% at 0.4-0.2 mg/kg).

Again the strong correlation (figure 2) between results from sample A and B (r 2 =0.99) and sample A and D (r 2 =0.88) indicates that the between-laboratory variation has a systematic component.

Insert figure 2

Concerning the results for chlormequat, there is more consistency in the results from the different laboratories. All but one laboratory obtained comparable results. However the one laboratory found systematically higher results than the others. It has not been possible to attribute differences in the results between the participating laboratories to the use of different methods or analytical principles.

Mepiquat. Results for mepiquat are listed in table 6. Laboratory 4 did not report results for mepiquat. For sample A, three laboratories had results that deviated less that 25% from the fortification level. One laboratory reported results 38% above the fortification level, one laboratory 141% above. For sample B and D, no laboratory reported results above their LOQ. The average within-laboratory precision for sample A is 14%. The between-laboratory precision is 50%, which is high compared to the Horwitz precision (18% at 0.4 mg/kg). As mepiquat was found in only one sample only, it has not been possible to test for systematic errors.