U Vincent

G Gizzi

Christoph Von Holst
email: christoph.von-holst@ec.europa.eu

J De Jong

J Michard

Validation of an analytical method for the determination of spiramycin, virginiamycin and tylosin in feedingstuffs by thin layer chromatography and bioautography

Keywords: Method validation, Microbiology, Screening -microbial screening Additives/Contaminants: Veterinary drug residues -antibiotics tylosin, virginiamycin, spiramycin, antibiotics, inter-laboratory comparison, feedingstuffs, thin layer chromatography, TLC

Validation of an analytical method for the determination of spiramycin, virginiamycin and tylosin in feedingstuffs by thin layer chromatography and bioautography

Christoph von Holst

Introduction

Prior to 1997, the antibiotics tylosin, virginiamycin and spiramycin were registered as feed additives in the European Union. However, since 1997, their use as feed additives has been prohibited, due to their possible contribution to bacterial resistance. In order to enforce the ban, there is need for reliable analytical methods that are suitable for official control purposes. Methods that were available in 2001 mainly focused on quantification of single compounds by means of microbiological inhibition tests (European Communities, 1972 for tylosin; European Communities, 1984a for virginiamycin; European Communities 1984b for spiramycin) or by means of HPLC with UV-detection [START_REF] Houglum | LC assay of tylosin in animal feeds[END_REF]Hajee et al. 2001). A multi-analyte method based on TLC and bioautography was published [START_REF] Gafner | Identification and semi-quantitative estimation of antibiotics added to complete 28 feeds, premixes and concentrates[END_REF], but this method mainly focused on additive levels. Moreover, none of the above methods was validated through an inter-laboratory study. Since there are no legal limits for the banned antibiotics in feedingstuffs, the emphasis of the method development and validation was placed on the correct identification of these compounds, carried out at relevant concentration levels. The objective of the European project SIMBAG-FEED (de [START_REF] De Jong | 5 the SIMBAG-FEED project[END_REF]) was to develop and validate such methods, preferably by means of a multi-analyte approach, since the analytical methods that were applied by laboratories until now did not meet all criteria, especially in terms of required sensitivity and specificity. The SIMBAG-FEED project developed various analytical methodologies, including methods for screening and confirmatory purposes. A step-wise approach was applied in order to meet this objective. In essence, after development the analytical methods were subjected to singlelaboratory validation to assess some performance characteristics. In the next step the transferability of the method to two other consortium laboratories was evaluated. Only, if the methods passed successfully these examinations they were considered as mature enough for the final step which focused on the validation of the method by conducting an inter-laboratory study. The major objective of this validation study was to assess important method performance characteristics when different laboratories apply the protocol to the same type of samples.

Here, we report the inter-laboratory validation of an analytical method that is based on thin layer chromatography (TLC) coupled to bio-autography, aiming at the detection of the antibiotics tylosin, spiramycin and virginiamycin. The purpose of the method is to screen samples for the presence of the target analytes in feed without giving a quantitative statement on their concentration. The required detection limit was set at 1 mg kg -1 of banned substances in feed, which is 5 times below the lowest contents formerly fixed by European legislation. Due to the combination of chromatography and bioautography this method has in principle a higher specificity compared to plate inhibition tests.

Therefore the method has the potential of post-screening in the case of a positive result from the microbiological plate analysis and before subjecting the sample to confirmatory analysis such as LC/MS.

Methods and Materials

Design of the study

For this study the laboratories were first involved in a training period consisting of a specific exercise on the method through audiovisual material (a CD-ROM with the method description), a training reporting sheet with a feedback questionnaire and test samples. The set of test samples had known content of the target analytes and blind samples. This was a specific exercise for the candidate -4-laboratories designed to get them familiar with the method protocol, to evaluate their effective performances on a limited number of samples and to check their rigorous application of the protocol.

In the second step the laboratories were involved in the validation period where they were asked to participate in the final inter-comparison trial.

Inter-comparison trial

In total 8 laboratories passed the training period and were therefore selected to participate in the validation study. The results reported by the laboratories were then used to obtain the final evaluation of the method in screening the banned antibiotics (spiramycin, tylosin and virginiamycin) in feedingstuffs for their official control.

The participants in the validation trial received a detailed method protocol, the 24 samples to be analysed and electronic forms to report the results of the analyses. The laboratories were asked to report on the presence of the banned antibiotics spiramycin, tylosin and virginiamycin. In this study the emphasis was placed on qualitative analyses and therefore only three responses to the various parameters were possible: (1) positive (substance is present), (2) negative (substance is not present) and

(3) no results. The latter response corresponded to inconsistent results or was indicated by laboratories when they could not report a result for a specific parameter.

At the end of the validation period results were collected and the data evaluation was performed followed by the statistical treatment.

Statistics

Since all results for this method were qualitative in nature, usual procedures for quantitative results were not applicable. In order to obtain a measure of the method performance, the results were analysed from different aspects. First, the straight results (positive, negative and no results) were calculated for the single test materials, thus looking at the overall results by considering the compound, its concentration and the matrix. Then, each target compound was examined as total number of correct positive, correct negative, false positive and false negative to identify at a glance the definitive performance of the method for each banned compound. Moreover, correct positive, correct negative, false positive and false negative were also calculated considering the compound, its concentration and -5-the matrix in order to look at the performance of the method not only for each banned substances but also at the chosen concentrations and in the different feed matrices.

The accuracy [START_REF] Langton | Analysing collaborative trials 15 for qualitative microbiological methods: accordance and concordance[END_REF] was then used to describe the capability of the method to correctly classify both positive and negative samples. In order to obtain this parameter the following equation was applied:

NA PD ND PA NA PA C Accuracy A + + + + =
where PA is the number of correct positive identifications (positive agreements), NA the number of correct negative identifications (negative agreements), PD the number of false positives (positive deviations) and ND the number of false negatives (negative deviations). The statistics were expressed as percentages after multiplication of the accuracy 100 (AC%). A score of 100 % means that all positive samples were correctly reported as positive and all negative samples were correctly reported as negative.

Since a score below 100 % means that part of the samples was incorrectly classified, it was of interest to know whether the reason of this result was a number of false positive or false negative results. Therefore, we also calculated the sensitivity (SE) and the specificity (SP) applying the following equations:

ND PA PA SE y Sensitivit + = NA PD NA SP y Specificit + =
The sensitivity expressed as percentage (SE%) is the ability of the method to classify a positive sample as positive, whereas the specificity also expressed as percentage (SP%) is the ability to classify a negative sample as negative. A criterion indicating sufficient performance was set for the sensitivity to be equal or above 95 %. For the TLC method validation 8 different materials were sent in blind triplicates (leading to 24 samples) to each participating laboratory. The composition of the test materials is shown in Table 1.

Test materials

The test materials were compound feeds for cattle, pig, poultry and calf containing typical ingredients such as corn, wheat, soya, wheat bran pellets, salts, and using a realistic recipe. Tylosin was obtained from Eli Lilly Liverpool (UK), spiramycin from Sigma Saint Louis (USA) and virginiamycin from Phibro, Rixensart (BE).The banned antibiotics were then mixed to the feedingstuffs in two steps. First, solutions from the target analytes in appropriate solvents were individually prepared to which soybean meal was added to obtain different pre-mixtures each of them containing one of the target analytes at a relatively high concentration of 180 mg/kg. Then, the solvents were removed by lyophilisation and the pre-mixtures fortified with the target analytes were mixed with the other ingredients to obtain the final test materials [START_REF] Kramer | Production of 4 11 blank and 10 spiked compound feeds for SCA SIMBAG-FEED[END_REF]).

The pure antibiotics were first tested for the identity, purity and content of the active compounds together with water determination and particle size analysis. Sufficient homogeneity of all pre-mixtures was confirmed by applying chemical analysis and microbiological inhibitions tests on each of the target analytes (von Holst, 2002). In addition, the fitness-for-purpose of the whole preparation procedure (i.e. the preparation of the final test samples using the pre-mixtures fortified with the target analytes and the feed ingredients) of the test material was confirmed in a separate experiment in which two feed samples containing the banned feed additives at the target level were analysed for all compounds by chemical analysis. The stability of the analytes in these two feed materials was also measured and they resulted stable during one month under specific conditions. In detail, the materials were stored at -20°C, 5°C, 20°C and 40°C for four weeks. The samples kept at -20°C were considered as reference point since we assumed that no degradation would take place at this temperature. The samples were considered as stable when the recovery rate of the target analytes was equal or above 95 % compared to the measured concentration in the reference samples. Sufficient values for the recovery rate were obtained for spiramycin at all temperatures, for tylosin at 20°C and below and for virginiamycin at -20°C. Based on these results the laboratories participating in the validation study were informed about appropriate storage conditions for the standards.

Finally, sufficient homogeneity of all test materials used in the inter-laboratory studies was investigated by conducting duplicate analyses of 10 randomly selected sample glasses and subjecting the obtained concentration to analysis of variance (ANOVA) The homogeneity principle was that if the test material was proven homogeneous for one banned compound, it also should be homogeneous for the other banned compounds since the preparation of the test material was identical for all compounds and matrices. This allows the analysis of only one of the compound present in each material in order to give homogeneity results (Serano et al. 2005).

As shown in Table 2, all the materials taken in consideration in this study resulted to be homogeneous on the basis of the ANOVA analysis. In fact the F-value in 7 out of 8 cases was lower compared to the "F critic". In our case "F critic" was 3.02 (10 groups and 2 counts per group). Calculating the sampling error of Mat 4 showed that this material is also fit for the intended purpose since the sampling error is below 50 % of the reference standard deviation of the study defined by the Horwitz equation. For material 1, 3, 4 and 5 the target analytes selected for the homogeneity study were others than those included in this particular validation exercise, since the SIMBAG-FEED project also covered avoparcin, bacitracin, carbadox and olaquindox. However, since the test materials were prepared for all analytes by the same procedure, the check for homogeneity was even possible on analytes that were not included in this exercise.

Method Protocol

The method makes it possible to detect and identify spiramycin, tylosin and virginiamycin in feedingstuffs, excluding mineral feeds and pre-mixtures. A detailed method description is given by Michard and Joubert, (2005) therefore this paper only contains a summary of the prototocol. The sample is extracted with a mixture of methanol and water and the target analytes partition into chloroform by subsequent liquid-liquid extraction. The chloroformic phase is concentrated and the concentrated feed extracts together with the reference spiked blank feeds extracts are subjected to thinlayer chromatography (TLC) on silica gel. Tylosin and spiramycin are separated on the same TLC plates using two different eluents (eluent 1 and 2) depending on the potential presence of other antibiotics in the samples, whereas virginiamycin is determined on a second TLC plate using a third eluent (eluent 3). Following the separation of the analytes by thin layer chromatography, bioautography is applied by pouring the antibiotic medium with the bacterial suspension (Micrococcus luteus) on the dried plates. After incubation over night the inhibition zones are visualised with a contrast solution.

The antibiotics are identified by comparing their retardation factor (Rf) values with those of the standard substances. The method protocol contains the Rf values of the target analytes obtained with the different eluents.

Results and Discussion

Training phase

The participants were asked to assess the presence or the absence of up to 3 antibiotics, in two unknown samples (MAT 2 and MAT 7). A discussion was open with the participants to address a number of specific problems which arose during the training phase. These were related both with the method itself and the way results were reported. Consequently the method protocol was modified for the final validation phase to enhance discrimination between the antibiotics. Moreover, new reporting sheets and experimental design were issued in order to ensure a sufficient number of results and limit the potential false interpretation of results. Overall, 9 out of 15 participating laboratories reported results and 8 laboratories were selected to take part into the following validation phase.

Inter-comparison trial

Seven out of 8 laboratories reported results for the final inter-comparison trial. The 24 samples per participating laboratory provided 147 valid results for spiramycin, 126 for tylosin and 168 for virginiamycin. The reported results of the individual laboratories are summarised in Table 3.

In Figure 1 the percentage of correct and false results from all materials for each compound are shown.

The rate of false negative results, which is the percentage of the total number of negative results was 15% for spiramycin, 3% for tylosin and of 2% for virginiamycin.

Please insert Figure 1 here.

The next set of graphs (Figure 2 to 4) shows the performance of the method for each single compound and additionally the effect of its concentration and the potential influence of the different feed matrices.

Please insert Figure 2 to 4 here

Looking more carefully at the results shows that the highest number of false negative is found in the lowest concentration of the banned compounds e.g. spiramycin 1 mg kg -1 in pig feed. Furthermore, the calf feed was also found to be a difficult matrix displaying false negative for spiramycin even at a concentration of 3 mg kg-1. In addition in two cases some materials have been excluded from the -9-evaluation for specific antibiotics. One case is related to a proven interference of virginiamycin on the determination of tylosin, if the samples contain both analytes. This is due to the fact that with eluent 1 and 2 tylosin and virginiamycin show the same Rf value, thus making it impossible to conclude which of these two analytes is in the sample when observing an inhibition zone at the relevant Rf value. By applying the eluent 3, virginiamycin is separated from tylosin, but tylosin does not elute (Rf = 0). However, the formation of an inhibition zone at the bottom edge of the plate does not allow for a proof of the presence of tylosin. Since in routine samples the simultaneous presence of tylosin and virginiamycin is in fact extremely rare, MAT 4 and MAT 7 (where both tylosin and virginiamycin are present) were excluded for the evaluation of the method for tylosin. In a second case, MAT 4 containing tylosin but not spiramycin was excluded from the evaluation of the results for spiramycin, since the 2nd factor of tylosin appears at the same Rf value as spiramycin. This effect is pronounced at elevated tylosin concentrations in the sample, viz. in MAT 4 containing 4 mg/kg of tylosin. This would lead to a higher number of false results for spiramycin, just in the unlikely case that the samples contain both target analytes. Summarising, for virginiamycin the results from all materials were taken into account, for spiramycin the results from MAT 1 to 3 and 5 to 8, and for tylosin the results from MAT 1 to 3, MAT 5, MAT 6 and MAT 8.

In Figures 5 to 7 the capability of the method to correctly classify positive and negative samples for each single banned compound is shown. The criterion indicating sufficient performance was set for the sensitivity (the ability of the method to classify a positive sample as positive) to be equal or above 95 %, allowing therefore a maximum of 5% rate of false negatives.

Please insert Figure 5 here

For spiramycin (Figure 5) the SE% ≥ ≥ ≥ ≥95% acceptance limit was always respected except for the pig feed at 1 mg kg -1 where SE% dropped to 71%. Since the lowest concentration was 2 mg/kg in cattle feed and since the in-house validation experiments did not reveal any influence of the specific matrix on the sensitivity of the method, we concluded that the limit of quantification for all matrices included is 2 mg kg -1 . Therefore the method is considered suitable for screening purposes at this concentration level or higher.

Please insert Figure 6 here For tylosin (Figure 6) the SE% ≥ ≥ ≥ ≥ 95% acceptance limit was achieved for all test materials analysed.

Both the AC% and SP% values were always 100% except for the blank calf feed (86%). However, this does not pose a major problem, since false positive results are eliminated by repeating the analysis applying appropriate confirmatory methods. The limit of detection of tylosin could therefore be determined to be 1 mg kg -1 in poultry feed. Following the same reasoning than for spiramycin and since no significant differences among matrices were proven during the in-house validation phase, these results also indicate that the method is fit for the purpose of screening tylosin in cattle, calf, poultry and pig feed at the minimum level of 1 mg kg -1 .

Please insert Figure 7 here

For virginiamycin (Figure 7) SE% ≥ ≥ ≥ ≥ 95% acceptance limit was always respected. The AC% was always above 95%. The specificity was 100% in poultry and 95% in calf and cattle feed. When taking into account the results obtained from the in-house validation period, it appears that the three matrices pig, cattle and poultry feed did not display a significant different behaviour regarding virginiamycin, whereas in some milk replacers (calf feed) the detection limit of virginiamycin can be slightly higher than 1 mg kg -1 as described in the method protocol. It can therefore be concluded from the intercomparison study that the method is fit for the purpose of screening virginiamycin in pig, poultry and cattle feed at the minimum level of 1 mg kg -1 . In calf feed, where the sensitivity was 100% for a concentration of 3 mg kg -1 , the LOD is most likely slightly above 1 mg/kg.

Another outcome of the collaborative study was the improvement of the method protocol. One major criterion that had to be taken into account for the final evaluation of the collaborative study results was the existence of interferences between the analytes. Indeed, virginiamycin interferes with the correct detection of tylosin and tylosin interferes at elevated concentrations with the correct identification of spiramycin. In practice, as the simultaneous presence of tylosin and virginiamycin for example in routine samples is extremely rare, the feed materials with this combination during the collaborative trial were excluded from the evaluation as appropriate. In consequence the method protocol was therefore amended to specify the Rf values for the target analytes with the three eluents utilised according to the method description and to alert the analyst to a possible interference of virginiamycin on the detection of tylosin. The modification was included after the validation study.

Conclusions

As a general conclusion and taking into account the in-house validation and inter-laboratory validation data, the collaborative study resulted in establishing the fitness-for-screening and/or post-screening purpose of spiramycin at a level of concentration of 2 mg kg -1 (expressed in microbiological activity) and of tylosin and virginiamycin at the target concentration of 1 mg kg -1 (expressed in microbiological activity) in feedingstuffs for poultry, pig, cattle and calf.

F

Figure 1 .Figure 2 .Figure 3 .Figure 4 .Figure 5 .Figure 6 .Figure 7 .Figure 1 :FoodFigure 2 :Figure 3 :Figure 4 :Figure 5 :Figure 6 :

 1234567123456 Figure 1. Percentage of the analytical results for each antibiotics. The results from all positive and all negative samples were pooled, respectively

Figure 7 :

 7 Figure 7: Virginiamycin: Sensitivity, specificity and accuracy per matrix compared to the target limit for accuracy (95 %)

Table 1 .

 1 Target concentrations of the antibiotics in the samples used in this validation study (all concentrations are expressed as microbiological activity in mg kg -1, as calculated from the declared microbiological activity of the specific antibiotic standard utilised in this study)

			Food Additives and Contaminants			Page 12 of 24
		MAT 1 MAT 2 MAT 3 MAT 4 MAT 5 MAT 6 MAT 7 MAT 8
	Feed matrix	Pig	Pig	Poultry Poultry	Calf	Cattle Cattle	Calf
	Spiramycin	1	5				2	4	3
	Tylosin phoshate Virginiamycin	o 4	2	1	4 1	3	2	5 5	3
		r
		P
			e e r
				R e v i e w
						O n
							l y
					-12-

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Table 2 .

 2 Summary of the homogeneity study of the samples used in the SIMBAG-Feed project (the concentrations of zinc bacitracin and spiramycin are expressed in microbiological activity in mg kg -1 ; the concentrations of carbadox and olaquindox are expressed on a gravimetric basis in mg kg -1 ; all

	measurements were performed by chemical analysis). LC-UV: Liquid chromatography coupled to UV
	detector; LC-MS/MS: Liquid chromatography coupled to a triple quadrupole mass spectrometer.
	Critical F-value: 3.02
	Material Feed	Compound	Analytical	F-value	Target	Measured
			analysed	method		concentration	Concentration
				applied		(mg kg -1 )	(mg kg -1 )
	1	Pig	Zinc	LC-MS/MS	1.15	5.0	5.7
			Bacitracin
	2	Pig	Spiramycin	LC-MS/MS	1.86	5.0	5.3
	3	Poultry Carbadox	LC-UV	2.60	4.0	4.6
	4	Poultry Olaquindox	LC-UV	8.90	12.0	12.0
	5	Calf	Olaquindox	LC-UV	1.10	3.0	3.0
	6	Cattle	Spiramycin	LC-MS/MS	0.33	2.0	1.8
	7	Cattle	Spiramycin	LC-MS/MS	1.72	4.0	3.5
	8	Calf	Spiramycin	LC-MS/MS	0.22	3.0	2.5

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Acknowledgements

The authors would like to thank the different institutes participating in this ring trial, more specifically: DGCCRF-L35 (Rennes, France); Bayerisches Landesamt für Gesundheid und Lebensmittelsicherheit (Oberschleissheim, Germany); LUFA-ITL (Kiel, Germany); LUFA Dep. Microbiology (Speyer, Germany); Istit. Zoo.Sper. Lobardia E. Romagna. Bromat. Feeds Lab. (Brescia, Italy); AGES (Wien, Österreich); EZN INIAP (Vale de Santarem, Portugal). The SIMBAG-FEED project was funded by the European Commission, Direction General RTD, 5 th Framework Programme, Competitive and Sustainable Growth (GROWTH) Programme, Measurements and Testing generic activity, Contract no.

G6RD-CT-2000-00413. We are also very grateful to Gerald Kramer (IRMM) for the test samples prepared within this project and utilised in the present study.

-24-Hajee, CAJ., van Rhijn, JA., Lasaroms, JJP., Keukens, HJ., de Jong, J., 2001, Development and 1 validation of a method for the determination of sub-additive levels of virginiamycin in compound 2 animal feeds by liquid chromatography. Analyst 126: 1332-1338


A Błaszczyk

J Skolimowski

Evaluation of the genotoxic and antioxidant effects of two novel feed additives (ethoxyquin complexes with flavonoids) by comet assay and micronucleus test

Keywords: ethoxyquin, flavonoids, hydrogen peroxide, comet assay, micronucleus test, human lymphocytes

The complexes of antioxidant ethoxyquin (1,2-dihydro-6-ethoxy-2,2,4trimethylquinoline, EQ) with rutin or quercetin (EQ-R and EQ-Q, respectively), were studied on human lymphocytes for genotoxic and antioxidant activities with the use of the comet assay and the micronucleus test. The study was undertaken to search for new potential antioxidants and was motivated by reports of unfavourable side-effects observed in animals fed with feeds containing EQ, which is allowed up to 150 mg kg -1 (0.015%) in complete animal feed. It was shown that EQ-R induced DNA damage in human lymphocytes when it was used at all the concentrations studied (1-25 µM), while after EQ-Q treatment the genotoxic effect was observed mainly after higher doses (10 and 25 µM). Increase in the number of micronuclei was observed only for EQ-Q after the dose of 50 µM. The studied compounds decreased the degree of DNA damage induced by HP (10 µM) in the comet assay. The results obtained in both tests showed that antioxidant activity of EQ-Q was comparable with that of EQ, so further detailed studies are necessary to estimate its possible usefulness as a feed preservative.

Introduction

In this paper the results of studies on genotoxicity and antioxidant activity of ethoxyquin (EQ) complexes with natural antioxidants: rutin and quercetin (EQ-R and EQ-Q, respectively) are presented. Ethoxyquin (1,2-dihydro-6-ethoxy-2,2,4trimethylquinoline, EQ) is a synthetic compound characterized by antioxidant activity which was originally developed as a rubber stabilizer. Later the Monsanto Corporation (USA) refined it for the use in small amounts as a preservative in animal feeds. In animal feed it is allowed up to 150 mg kg -1 (0.015%) (http://www.cfsan.

fda.gov/~dms/opa-appa.html). In many poultry farms EQ is also added to drinking water because it makes the egg yolk a brighter yellow. EQ is also used for colour preserving of chili powder, ground chili, and paprika up to 100 mg kg -1 (http://www.cfsan.fda.gov/~dms/opa-appa.html). It is assigned a toxicity rating of 3 or "moderately toxic", and this toxicity rating is slightly greater than ratings for tetracycline and penicillin. Susceptibility of laboratory animals to EQ toxicity increases with the nutritional stress caused by the changes of dietary constituents, e.g. fat. In the late 1980s many companies began adding extra EQ to animal feeds because it contained much fat and EQ was the cheapest and most effective in extending the shelf life of these products. After that, unusual disorders were observed in animals, mainly in dogs [START_REF] Dzanis | Safety of ethoxyquin in dog foods[END_REF]. In different experiments it was shown that this compound caused weight loss, increase in the mass of liver and kidney, accumulation of lipids in kidney and also pre-neoplastic lesions in the urinary bladder and kidney [START_REF] Miyata | Short-term screening of promoters of bladder carcinogenesis in N-butyl-N-(4hydroxylbutyl) nitrosamineinitiated, unilaterally ureter-ligated rats[END_REF][START_REF] Manson | Ethoxyquin alone induces preneoplastic changes in rat kidney whilst preventing induction of such lesions in liver by aflatoxin B 1[END_REF][START_REF] Little | Chemical Committee Draft Report[END_REF]. Adverse effects were also noted in people professionally exposed to this compound [START_REF] Rubel | Allergic contact dermatitis to ethoxyquin in a farmer handling chicken feeds[END_REF]. In 1997 U.S.

Food and Drug Administration (FDA) after reviewing a study done by Monsanto felt that using EQ up to 150 mg kg -1 might not provide a sufficient margin of safety in animals and asked manufacturers for voluntary lowering the maximum amount of EQ in feed to 75 mg kg -1 (0.0075%) (http://www.fda.gov/ cvm/september97.htm). The harmful effects of EQ caused its nomination by the U.S. Food and Drug Administration (FDA) for carcinogenicity testing as well as genotoxicity studies in mammalian systems were also recommended (Drewhurst, 1998). Recently, the ability of EQ to cause DNA damage in human lymphocytes has been stated [START_REF] Błaszczyk | DNA damage induced by ethoxyquin in human peripheral lymphocytes[END_REF][START_REF] Błaszczyk | Comparative analysis of cytotoxic, genotoxic and antioxidant effects of 2,2,4,7-tetramethyl-1,2,3,4-tetrahydroquinoline and ethoxyquin on human lymphocytes[END_REF].

Due to harmful effects observed in animals after feeding them with EQ containing feeds, new antioxidant compounds, including EQ analogues and also complexes of two biologically active molecules which could replace EQ have been sought [START_REF] Metodieva | Rutoxyl(rutin/4acetamide-1-hydroxy-2,2,6,6-tetramethylpiperidinium) is a new member of the class of semi-natural products of high pharmacological potency[END_REF]Dorey et al., 2000;[START_REF] Koning | The antioxidant ethoxyquin and its analogues: a review[END_REF]Błaszczyk and Skolimowski, 2005a).

Synthesis of the complexes of EQ with rutin or quercetin was prompted by the hope that EQ and the flavonoids in such combinations could exhibit stronger antioxidant activity than each of them separately. Until now, only antioxidant properties of EQ-R have been studied; it was shown that this complex effectively prevented evening primose oil from oxidation, but this activity was not compared with that of EQ [START_REF] Skolimowska | Effect of rutin and complex ethoxyquin-rutin on the stability of Oenothera paradoxa oil[END_REF].

The genotoxicity of EQ complexes with rutin and quercetin have not been studied so far but they were earlier studied as to their cytotoxicity (Błaszczyk and Skolimowski, 2005a). It was shown that both EQ-R and EQ-Q induced apoptosis in cultured human lymphocytes and decreased viability of treated cells, but not so efficiently as EQ, so the flavonoids added to the EQ molecule modulated cytotoxic effects caused by EQ alone.

The aim of the present study was to determine the genotoxicity and antioxidant activitity of the complexes of EQ with rutin (EQ-R) or quercetin (EQ-Q) in human peripheral lymphocytes and to compare them with the results obtained earlier for EQ [START_REF] Błaszczyk | Comparative analysis of cytotoxic, genotoxic and antioxidant effects of 2,2,4,7-tetramethyl-1,2,3,4-tetrahydroquinoline and ethoxyquin on human lymphocytes[END_REF]. The comet assay (alkaline single cell gel electrophoresis assay) and the micronucleus test were used in the experiments.

Material and methods

Chemicals

The complexes of ethoxyquin (EQ, 1,2-dihydro-6-ethoxy-

Lymphocyte isolation

Lymphocytes were isolated from peripheral blood of healthy female non-smoking volunteers. According to the donors' declarations they were not exposed to radiation or drugs for six months prior to the experiment.. The isolation of lymphocytes was performed by centrifugation in a density gradient of Histopaque 1077 (15 min, 280 x g).

The viability of the isolated lymphocytes was measured by trypan blue exclusion assay and was found to be about 99%. In the comet assay the final concentration of the cells was adjusted to about 2 x 10 5 lymphocytes per ml by adding RPMI 1640 medium to the cell suspension. In the micronucleus test the number of lymphocytes per ml of the culture medium was about 0.8 x 10 6 .

Comet assay

For the genotoxicity studies the isolated lymphocytes suspended in RPMI 1640 medium were treated with the tested compounds (EQ-R or EQ-Q) for 1h at 37°C. The compounds were dissolved in ethanol (ET; the solvent concentration: 0.05% v/v) and used at five concentrations ranging from 1 to 25 µM (i.e. 0.02 -5 µg/ml).

For the antioxidant activity evaluation the compounds tested were added to the lymphocyte suspensions at the concentrations ranging from 1 to 10 µM. Immediately after this the cells were treated with hydrogen peroxide (10 µM) for 5 min. on ice. Three experiments, each with the use of the cells obtained from one donor were performed and in each of them duplicate assays were carried out for all concentrations of the compounds tested. After the treatment the lymphocytes were washed in PBS and cell viability was determined with the use of 0.4% trypan blue reagent.

The procedure of [START_REF] Singh | A simple technique for quantification of low levels of DNA damage in individual cells[END_REF] was applied to perform the alkaline comet assay.

The lymphocytes suspended in 0.75% LMP agarose were spread onto microscope slides precoated with 0.5% NMP agarose. The cells were then lysed for 1 h at 4 o C in a solution consisting of 2.5 M NaCl, 100 mM EDTA, 10 mM Tris, 1% N-lauroylsarcosine (pH 10) and 1% Triton X-100 added just prior to use. After the lysis the slides were incubated in alkaline (pH > 13) electrophoresis buffer (1mM EDTA, 300 mM NaOH)

for 30 min at 4 o C. Then electrophoresis was carried out at 25 V (0.73 V/cm) and 300 mA for 23 min. The slides were then rinsed with 0.4 M Tris-HCL for 15 min, pH 7.5 at 4 o C. After neutralization the gels were dried and stored for analysis. The entire procedure was performed under dim light. The slides were stained with DAPI (1 µg/ ml) in the dark at 4 o C, and examined using a fluorescence microscope (Olympus BX60F5). Image analysis was performed with the CASP software [START_REF] Końca | A cross-platform public domain PC image-analysis program for the comet assay[END_REF].

In each experiment 100 randomly selected cells (50 cells from each sample) were used to evaluate the DNA damage for each concentration of the tested compounds. The percentage of DNA in the tail, showing extent of DNA damage, was analysed.

Statistical analysis was performed by the use of Student's t-test. Correlation coefficients were calculated to analyse dose-response relationships. The cytokinesis block micronucleus assay (CBNM) was carried out using the technique proposed by [START_REF] Fenech | The cytokinesis-block micronucleus technique: A detailed description of the method and its application to genotoxicity studies in human populations[END_REF] with slight modifications. Isolated human lymphocytes were placed in RPMI 1640 medium supplemented with 15% foetal calf serum, 1% penicillin/streptomycin solution and 1% phytohaemagglutinin M and incubated for 24 h at 37°C. Then EQ-R or EQ-Q were added (5 -50 µM, i.e. 1 -10 µg/ml) and maintained until cell harvest to estimate their genotoxic activities. To analyse antioxidant potencies of the compounds hydrogen peroxide (HP) at the concentration of 75 µM was added to the cultures simultaneously with EQ-R or EQ-Q. Cytochalasin-B was added (4.5 µg/ml) 44 h after PHA stimulation. The cultures were harvested 28 h later, giving the total culture time of 72 h. Micronuclei preparation was performed with 75 mM KCl as hypotonic treatment and fixation with acetic acid-methanol (1 : 5, v/v). Air dried preparations were made and the slides were stained with 3% Giemsa.

Each compound was tested using the cells obtained from three donors. For each experimental point, 3000 binucleated cells with well preserved cytoplasm were scored (1000 cells from replicate cultures in each experiment). Micronuclei were analysed in accordance with the criteria of [START_REF] Fenech | The cytokinesis-block micronucleus technique: A detailed description of the method and its application to genotoxicity studies in human populations[END_REF]. Five hundred cells were also scored to calculate a cytokinesis block proliferation index (CPBI) according to the formula:

CPBI = (M 1 + 2M 2 + 3M m )/N
where M 1 , M 2 , M m represent the number of cells with one, two nuclei or the number of multinucleate cells, respectively, and N is the number of cells scored (Kirsch-Volders et al., 2003). Statistical analysis was made using the χ 2 test.

Results

Comet assay

Since toxicity may cause DNA damage, preliminary studies were performed with the use of trypan blue exclusion assay to determine the viability of the cells after treatment with the studied compounds. Both in the genotoxicity analysis and in antioxidant activity measurements the viability of the cells after the treatment with the compounds at all the concentrations used in these studies was higher than 90%.

Figure 1 presents the results of the comet assay after treatment with EQ-R and EQ-Q used at five concentrations (1 -25 µM). It was shown that both compounds caused statistically significant increase in the mean percentages of DNA in the comet tail in comparison with the control (except for EQ-Q at the concentrations of 2.5 and 5 µM), and dose-effect dependence was seen for EQ-R (r = 0.75). EQ-Q was a weaker inducer of DNA damage than EQ-R. The difference between EQ-Q and EQ-R activities was statistically significant, but at the highest concentration (25 µM) both compounds were similarly strongly genotoxic.

[Insert Figure 1 about here]

As seen in Figure 2 the complexes of EQ with the flavonoids protected lymphocytes from the genotoxic effects of HP; after HP treatment together with EQ-Q or EQ-R the statistically significant reduction of DNA damage in comparison with the positive control (HP treatment) was observed. EQ-Q was more effective in protecting the lymphocytes against HP-induced DNA damage when the concentrations 2.5 and 10.0 µM were compared, but the difference between EQ-R and EQ-Q antioxidant activities was statistically significant only at the 10 µM dose.

[Insert Figure 2 about here]

Micronucleus test

Preliminary experiments indicated that the dose of 50 µM was the highest non-toxic concentration after which cells with well-preserved cytoplasm could be obtained. In the present study four concentrations were used (1-50 µM) to assess mutagenicity and antioxidant activity of EQ-R and EQ-Q. As seen in Table I EQ-R did not influence the cell divisions as the values of CPBI were not significantly different from the control.

After EQ-Q treatment the decrease in the value of CPBI was seen after the concentration of 50 µM, especially in the cultures of lymphocytes obtained from donor B and C.

[Insert Table I about here]

The results reported in Table I also show that only EQ-Q induced statistically significant increase in the frequency of micronuclei as compared to the control (20.3 versus 9.7) micronuclei per 1000 binucleated cells) and such an effect was observed after the concentration of 50 µM. The lower doses of EQ-Q induced a moderate number of micronuclei and this was not significantly greater than in the control. EQ-R did not induce statistically significant increase in the number of micronuclei (Table I).

[Insert hydrogen peroxide (HP) and EQ-R or EQ-Q. Preliminary experiments with HP showed that this compound effectively induced micronuclei at the concentration of 75 µM dose (no significant cell division inhibition was observed). The present experiments showed that EQ-R did not protect the cells from damage induced by HP (Table II). After treatment with HP and EQ-R as many micronuclei as after HP alone were observed (or even slightly more after EQ-R at concentrations of 25-50 µM). The protective effect was produced by EQ-Q but only at the two lower doses (5 µM and 10 µM; Table II).

Table II also shows that the tested compounds used together with HP slightly inhibited cell divisions. The compounds reduced CPBI values, especially when the higher doses were used.

Discussion

Ethoxyquin is a strong antioxidant widely used mainly in animal feeds and also in various food products (for example in fish food, canned pet food, and in spices to preserve colour or to control scald in apple and pear), but because of adverse health effects observed in animals and humans exposed to it, new compounds with strong antioxidant activity which could replace EQ are intensively searched (Dorey et al., 2000;[START_REF] Koning | The antioxidant ethoxyquin and its analogues: a review[END_REF]. In our laboratory two new compounds, complexes of EQ with rutin (EQ-R) or quercetin (EQ-Q), were synthesized. In the earlier experiments, these compounds were studied using the trypan blue exclusion assay and the TUNEL method, which allows detection of early stages of apoptosis by labelling 3'OH ends of fragmented DNA (Błaszczyk and Skolimowski, 2005b). It was shown that EQ-R and 12 EQ-Q effectively induced apoptosis in human lymphocytes after 24-h treatment, especially at three higher concentrations studied (100, 250 and 500 µM), but their effect was significantly weaker than that of EQ (Błaszczyk and Skolimowski, 2005b). In the present study the genotoxic and antioxidant activities of EQ-R and EQ-Q were evaluated in comparison with the properties of EQ.

The genotoxicity of EQ-R and EQ-Q has not been studied so far. In the present study the comet assay showed that these two new compounds caused DNA fragmentation and that EQ-Q was a significantly weaker inducer of DNA damage than EQ-R. On the other hand, in micronucleus assay the positive result was not observed, except for the highest dose of EQ-Q (50 µM). That discrepancy between the results of the tests used in this study can be due to the fact that the comet assay is significantly more sensitive in detecting low levels of DNA damage than micronucleus test [START_REF] He | Comparative evaluation of the in vitro micronucleus test and the comet assay for the detection of genotoxic effects of Xray radiation[END_REF].

Moreover, the comet assay was performed on the resting cells, whereas in the micronucleus assay the proliferating cells were studied which have higher repair capacity than cells in G 0 phase of the cell cycle [START_REF] Kalweit | Liquid-holding experiments with human lymphocytes; III experiment with G 0 and G 1 cells[END_REF]. So in the micronucleus assay primary DNA lesions (which were detected in the comet assay) could be repaired and they are not turned into fixed mutation.

The comparison of the obtained results with the genotoxicity of EQ studied earlier [START_REF] Błaszczyk | DNA damage induced by ethoxyquin in human peripheral lymphocytes[END_REF][START_REF] Błaszczyk | Comparative analysis of cytotoxic, genotoxic and antioxidant effects of 2,2,4,7-tetramethyl-1,2,3,4-tetrahydroquinoline and ethoxyquin on human lymphocytes[END_REF] shows that modifications of the EQ molecule changed its genotoxic properties; the complexes of EQ with flavonoids

were not so strongly genotoxic as EQ and it can be an important property for the potential preservatives. In Table III the potency of EQ-R, EQ-Q and EQ to induce DNA fragmentation and micronuclei formation is shown. The difference between the 13 activities of the compounds was clearly seen in the comet assay: EQ was the most genotoxic agent. In the micronucleus test the micronuclei-inducing potencies were low and similar for the all compounds, as they did not reveal clear mutagenic effects.

[Insert Table III about here] The synthesis of the complexes of EQ with the flavonoids (rutin and quercetin) which are natural antioxidants was motivated by the hope that the combination of two active molecules could result in an increased antioxidative effect. So far, only the antioxidant activity of EQ-R has been studied [START_REF] Skolimowska | Effect of rutin and complex ethoxyquin-rutin on the stability of Oenothera paradoxa oil[END_REF] and it was shown that this complex effectively prevented evening primose oil from oxidation. The present study revealed in the comet assay the protective properties of the complexes of EQ with the flavonoids against HP-induced DNA fragmentation; the antioxidant activity of EQ-Q was higher than that of EQ-R but the difference was not statistically significant. The difference in the antioxidant potency of the studied compounds was also seen in the micronucleus assay. The comparison of the present results in both tests performed with those obtained earlier for EQ [START_REF] Błaszczyk | Comparative analysis of cytotoxic, genotoxic and antioxidant effects of 2,2,4,7-tetramethyl-1,2,3,4-tetrahydroquinoline and ethoxyquin on human lymphocytes[END_REF] shows that EQ-R is a compound with much weaker antioxidant potency (Table III). On the other hand antioxidant activity of EQ-Q in the comet assay was relatively high (except for the lowest concentration used), and in the micronucleus assay it was also efficient similarly as that of EQ [START_REF] Błaszczyk | Comparative analysis of cytotoxic, genotoxic and antioxidant effects of 2,2,4,7-tetramethyl-1,2,3,4-tetrahydroquinoline and ethoxyquin on human lymphocytes[END_REF].

In conclusion, the present results showed that flavonoids added to the EQ molecule modified its genotoxic properties. The complexes of EQ with flavonoids protected human lymphocytes from genotoxic effects induced by HP but the protective effects were weaker (especially for EQ-R) than those observed after EQ treatments. EQ-Q was the least genotoxic and its antioxidant activity was relatively high. Further detailed studies on EQ-Q antioxidant properties are necessary to estimate its possible usefulness as feed preservative. The reduction (%) showing antigenotoxicity was calculated using the formula: (mean score in A -mean score in B/mean score in A-mean score in C) x 100, where A is the treatment with HP, B is the treatment with HP plus the tested compound, C is the negative control. b EQ data for the comparison were taken from earlier published results [START_REF] Błaszczyk | Comparative analysis of cytotoxic, genotoxic and antioxidant effects of 2,2,4,7-tetramethyl-1,2,3,4-tetrahydroquinoline and ethoxyquin on human lymphocytes[END_REF]). c Mean percentages of DNA in the tail were compared. d The numbers of micronuclei (MN) were compared. e The concentration not assayed. * The statistically significant difference between EQ-R or EQ-Q and EQ treatments (P < 0.05).

F

  Evaluation of the genotoxic and antioxidant effects of two novel feed additives (ethoxyquin complexes with flavonoids) by comet assay and micronucleus test

Figure 1 .Figure 2 .

 12 Figure 1. The results of the genotoxicity testing by the comet assay expressed as mean percentages of DNA in the comet tail ± S.E.M. Human lymphocytes were incubated with the tested compounds for 1 h. ET: the negative control with ethanol (ET; 0.05% v/v). C: the negative control without any treatment. * Significantly different from the negative ethanol control (P < 0.05). 190x254mm (96 x 96 DPI)

Table

  Table II about here] II presents the results observed after the treatment of human lymphocytes with

	F o r
	P
	e
	e r
	R
	e
	v i e
	w
	O n l
	y
	11

Table I .

 I Induction of micronuclei (MN) and CBPI values in human lymphocytes treated with complexes of EQ with flavonoids (EQF) for 48 h.

	Donor		Treatment		EQ-R	EQ-Q
				MN			CBPI	MN	CBPI
	A		Control	6			1.98	6	1.98
			ET (0.05% v/v)	9			1.77	9	1.77
			EQF 5 µM	9			1.73	9	2.04
			EQF 10 µM	8			1.79	12	1.81
	B	o r F o r F o r EQF 25 µM EQF 50 µM Control ET (0.05% v/v) F o r	6 7 9 9			1.57 1.40 2.12 2.17	9 20 * 9 9	1.76 1.50 2.12 2.17
			P e e r P e e r P e e r EQF 5 µM 9 P EQF 10 µM 14 EQF 25 µM 15 e EQF 50 µM 16 e r			2.13 2.17 2.02 1.85	10 9 19 20 *	1.81 1.73 1.63 1.29
	C		Control ET (0.05% v/v)	R R R 10 11 R		1.96 1.80	10 11	1.96 1.80
			EQF 5 µM	e e e 11 e	1.92	11	1.85
			EQF 10 µM EQF 25 µM EQF 50 µM	12 12 11	v i e v i e v i e 1.78 1.80 1.69 v i e	12 14 21	1.73 1.57 1.31
	Total (A+B+C)		Control ET (0.05% v/v)	8.3 ± 2.1 9.7 ± 1.2	w w w 2.02 ± 0.09 1.91 ± 0.22 w	8.3 ± 2.1 9.7 ± 1.2	2.05 ± 0.10 1.97 ± 0.28
	(mean ± SD)	EQF 5 µM EQF 10 µM EQF 25 µM EQF 50 µM	O n l O n l O n l 9.7 ± 1.2 1.93 ± 0.20 10.0 ± 1.0 11.3 ± 3.1 1.91 ± 0.22 11.0 ± 1.7 11.0 ± 4.6 1.80 ± 0.23 14.0 ± 5.1 11.3 ± 4.5 1.52 ± 0.29 20.3 ± 0.3 * O n l	1.90 ± 0.12 1.76 ± 0.05 1.65 ± 0.10 1.37 ± 0.12 *
							y y y y
	MN, micronuclei; CPBI, cytokinesis-block proliferation index; EQF, complexes of EQ with
	flavonoids, rutin (EQ-R) or quercetin (EQ-Q). ET, the control with ethanol used as a solvent
	(0.5%, v/v).
	* The statistically significant difference as compared with the negative control (P < 0.05).

Table II .

 II The effect of complexes of EQ with flavonoids (EQF) on HP genotoxicity assessed by the micronucleus assay in human lymphocytes.

	Donor	Treatment	EQ-R	EQ-Q
			MN	CBPI	MN	CBPI
	A	Control	6	1.62	13		1.55
		ET (0.05% v/v)	7	1.59	12		1.52
		HP (75 µM) a	20 *	1.52	24 *		1.58
		HP + EQF (5 µM) HP + EQF (10 µM) HP + EQF (25 µM) HP + EQF (50 µM) F o r	17 21 28 33	1.53 1.37 1.39 1.19	11 ** 12 ** 18 20		1.51 1.40 1.37 1.20
	B	Control ET (0.05% v/v) HP (75 µM) a P HP + EQF (5 µM) e HP + EQF (10 µM) HP + EQF (25 µM) e r 9 9 15 13 13 17	1.56 1,52 1.69 1.55 1.39 1.59	11 9 23 * 12 * 8 * 24		2.06 1.89 1.88 1.95 1.80 1.81
	C	HP + EQF (50 µM) Control ET (0.05% v/v)	13 11 R 10 e	1.24 1.60 1.62	22 11 10	1.60 1.62	1.50
		HP (75 µM) a HP + EQF (5 µM) HP + EQF (10 µM) HP + EQF (25 µM) HP + EQF (50 µM)	25 * 18 19 v i 1.71 1.58 1.40 e 23 1.44 28 1.58 w	25 * 12 ** 11 ** 25 26	1.71 1.47 1.47 1.34 1.26
	Total (A+B+C) (mean ± SD) HP (75 µM) a Control ET (0.05% v/v) HP + EQF (5 µM) HP + EQF (10 µM)	8.7 ± 2,5 8.7 ± 1.5 20.0 ± 5.0 * 1.64 ± 0.10 1.59 ± 0.03 1.58 ± 0.05 16.0 ± 2.6 1.55 ± 0.03 O n 11.7 ± 1.2 10.3 ± 1.5 24.0 ± 1.0 * l 11.7 ± 0.6 ** 17.7 ± 4.2 1.39 ± 0.01 10.3 ± 2.1 ** y	1.74 ± 0.28 1.68 ± 0.19 1.72 ± 0.15 1.64 ± 0.27 1.56 ± 0.21
		HP + EQF (25 µM)	22.7 ± 5.5	1.47 ± 0.10	22.3 ± 3.8	1.51 ± 0.26
		HP + EQF (50 µM)	24.7 ± 10.4 1.34 ± 0.21	22.7 ± 3.1	1.32 ± 0.16
	MN, micronuclei; CPBI, cytokinesis-block proliferation index; EQF; complexes of EQ with flavonoids,

rutin (EQ-R) or quercetin (EQ-Q). a Hydrogen peroxide (HP) added to the cultures together with ethanol (ET, the solvent of EQ-R and EQ-Q). * Significantly different from the negative control (P < 0.05). ** Significantly different from the positive control (P < 0.05).

Table III .

 III Comparison of the genotoxicity and antioxidant activity of the tested compounds (EQ-R and EQ-Q) with EQ data taken from the earlier published results[START_REF] Błaszczyk | Comparative analysis of cytotoxic, genotoxic and antioxidant effects of 2,2,4,7-tetramethyl-1,2,3,4-tetrahydroquinoline and ethoxyquin on human lymphocytes[END_REF].

	Concentration	Genotoxicity	Antioxidant activity:
	(µM)				Reduction (%) a
		EQ/EQ-R	EQ/EQ-Q	EQ-R	EQ-Q	EQ b
		ratio b	ratio b
	Comet assay c
	0	1.05	1.05
	1	1.29	2.83 *	44.4	23.4 *	51.8
	2.5	1.60	3.21 *	31.8	62.9	55.9
	5	1.16	3.73 *	49.6	50.8	59.7
	10	1.46 *	3.40 *	15.2 *	56.2	59.7
	25	1.60 *	1.89 *	NA e	NA	NA
	Micronucleus test d
	0	0.88	0.88
	5	0.93	0.90	35.4	89.8	66.7
	10	0.84	0.86	20.4	100.0	66.7
	25	1.00	0.76	0.0	12.4	0.0
	50	1.02	0.57 *	0.0	9.5	4.2
	a

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

Dorey G, Lockhart B, Lestage P, Casara P, 2000. New quinolinic derivatives as centrally active antioxidants. Bioorganic and Medicinal Chemistry Letters 10:935-

Acknowledgements

We are grateful to Aleksandra Wołczańska and Danuta Paszkiewicz for technical assistance. This work was supported by the State Committee for Scientific Research (KBN, Poland), grant number 3 PO4C 021 24.


Panagiotis R Georgakopoulos

Evaggelia Foteinopoulou

P E Athanasopoulos

Eleftherios H Drosinos

Panagiotis N Skandamis

Panagiotis ; Georgakopoulos

Keywords: matrix effect, organophosphorus pesticide residue analysis, ethyl acetate, 29 botanical groups, validation

published or not. The documents may come

Studying the recoveries of four representative organophosphorus pesticides from eighteen plant products belonging to different botanical categories;

implications for matrix effects

Bearing in mind the prevalence of chemical pest control and the wide variety of 32 pesticides available, the monitoring of pesticides residues constitutes a prevalent 33 objective in chemical contaminants research that aims mainly to prevent possible risks 34 for human health. A large number of Multiresidue Extraction Methods (MRMs) is 35 applied in pesticide residue analysis, all of which offer an effective way of 36 identification and quantification of several analytes in a relatively short period 37 [START_REF] Hajšlová | Matrix -induced effects: a critical point in the gas chromatographic 374 analysis of pesticide residues[END_REF]. According to the EU guidance [START_REF] Hill | Guidelines for in -house validation of analytical 378 methods for pesticide residues in food and animal feeds[END_REF], 38 recovery portions of target pesticides form a minimum requirement in order to 39 validate the analytical method, necessitating the availability of recovery data from 40 various pesticides and representative sample matrices (with varying chemical 41 composition and botanical characteristics) of different plant product categories. One 42 of the most frequently used methods in the analysis of non fatty matrices is the 43 extraction with ethyl acetate and gas chromatography with appropriate sensitive 44 detectors (Ministry of Welfare, 1988), while small modifications, especially in the 45 additional clean-up step, are nowadays also widely used, with acceptable recoveries 46 of pesticides [START_REF] Cai | Rapid multiresidue screening method for 348 organophosphate pesticides in vegetables[END_REF][START_REF] Dorea | Determination of organophosphorus 354 pesticide residues in fruits by gas chromatography with ITD and NPD detection[END_REF][START_REF] Hajšlová | Matrix -induced effects: a critical point in the gas chromatographic 374 analysis of pesticide residues[END_REF]Navarro et al. 47 2002;[START_REF] Pugliese | Gas 390 chromatographic evaluation of pesticide residue contents in nectarines after non-391 toxic washing treatments[END_REF]. 48 However, the application of MRMs has several difficulties, the main of which are 49 the suitability/compatibility of the extraction solvent to the analyzed pesticides and 50 the influence of each matrix examined on the analysis. Particularly, there have been 51

observed differences in the pesticides recovery depending on the solvent used in the 52 sample preparation [START_REF] Maštovská | Evaluation of common organic solvents for gas 381 chromatographic analysis and stability of multiclass pesticide residues[END_REF]. In addition, the 53 quantification/recovery of the most important analytes by gas chromatography is 54 strongly affected by various factors, including the efficiency of the extraction method 55 and a phenomenon, known as "matrix-induced chromatographic response 56 enhancement", which was first described by [START_REF] Erney | Explanation of the matrix -366 induced chromatographic response enhancement of organophosphorus pesticides 367 matrix effects in the analysis of pesticides[END_REF], and causes 57 excessively high recovery results. This phenomenon takes place during analysis of 58 samples that contain a wide range of matrix components (e.g. pigments, waxes, lipids 59 and other non volatile constituents) that may remain after the preparation of the 60 sample and the additional step of clean-up (Godula et al. 1999). Such compounds 61 accumulate in the GC inlet and/or in the front part of a capillary column. Particularly, 62 during analysis of a pesticide(s) standard solution, more active sites in the injection 63 liner are available for the certain analyte(s), compared to those available during 64 analysis of a sample containing also matrix components (Schenck and Lehotay 2000). 65

This is due to the fact that the latter components block the active sites of injection 66 liner [START_REF] Erney | Explanation of the matrix -366 induced chromatographic response enhancement of organophosphorus pesticides 367 matrix effects in the analysis of pesticides[END_REF]. 67

Consequently, matrix effect is considered, nowadays, as one of the most persistent 68 sources of uncertainty in pesticide residue analysis [START_REF] Cuadros-Rodriguez | Assessment of uncertainty in 351 pesticide multiresidue analytical methods: main sources and estimation[END_REF]69 Egea Gonzalez et al. 2002). However, available studies have focused on collecting 70 recovery data of pesticides examining combinations of few primary crop products, 71 many pesticides and many fortification levels [START_REF] Dorea | Determination of organophosphorus 354 pesticide residues in fruits by gas chromatography with ITD and NPD detection[END_REF]Hajšlová et al. 72 1998). Other studies involve determination of the pesticides recovery by many 73 products belonging only to one plant commodity group [START_REF] Cai | Rapid multiresidue screening method for 348 organophosphate pesticides in vegetables[END_REF]Egea 74 Gonzalez et al. 2002). Therefore, there is need to comparatively evaluate various 75 matrices from various botanical categories per analytical method to determine the 76 uncertainty due to matrix effect. Moreover, the recovery studies commonly involve a 77 few matrices fortified with a mixture of pesticides. Various food matrices fortified 78 with one pesticide should also be included in pesticide recovery studies. This would 79 clearly illustrate the matrix effect per pesticide. 80 The objective of this work was the evaluation of the matrix effects on the recovery 81 of four commonly applied pesticides of different physicochemical properties 82 (especially polarity), fortified in plant products of various botanical categories, at 83 three indicative levels (0.2, 0.5 and 1.5mgkg -1 ) and MRL (when different from the 84 fortification level studied). 85 86

Materials and Methods 87

Materials and Reagents 88

The solvent used was ethyl acetate (Merck, Darmstadt, Germany, 110972) and was of 89 pesticide grade. Pesticide standards (chlorpyrifos, dimethoate, methamidophos and 90 methidathion) of more than 98% purity were obtained from Chem Service (Chem 91 Service, West Chester, PA, USA). Stock solutions were prepared in ethyl acetate and 92 working standard mixtures were obtained with appropriate dilutions before use. 93

Particularly, the standards were used for the preparation of stock standard solutions 94

for each pesticide at 100mgkg -1 in the used solvent and stored at -18 o C. In Table I, 95 there is the list of the investigated organophosphorus pesticides along with some of 96 their physicochemical characteristics [START_REF] Tomlin | The Pesticide Manual[END_REF]. Anhydrous sodium sulfate for 97 residue analysis was of pesticide grade (Riedel -de Haën, Hanover, Germany, 98 13464). 99

[Insert Table I about grapes and strawberries) were used as representative matrices in the experiment. 107

These commodities were checked by gas chromatography to ensure the absence of 108 pesticide residues and their suitability for the analysis. 109

Analytical Procedure 110

All samples were prepared in triplicate by a general method suitable for gas 111 chromatography analysis with a nitrogen-phosphorus detector (NPD) (Ministry of 112 Welfare 1988). According to the method, 50g of the representative homogenized 113 sample of each commodity were mixed with 100mL of ethyl acetate and 50g of 114 anhydrous sodium sulfate. The mixture was blended for 2min and the extract was 115 filtered through Whatman No 1 filter paper, containing approximately 5g of 116 anhydrous sodium sulfate, into a conical flask. The clear filtrate, without additional 117 clean-up, was stored at -20°C, until it was injected into the chromatograph. The 118 storage of freezed extracts ranged from 1-4 days, so that the bounding reactions can 119 be avoided. Clean-up was not performed because the standard, by which the method 120 was adopted (Ministry of Welfare 1988), suggests that additional clean-up steps after 121 extraction are not always required for non fatty substances like fruits and vegetables, 122 and especially for the pesticides used in our study. Furthermore, the use of an 123 additional clean-up procedure may reduce the amount of co-extractives (Hajšlová et 124 al. 1998;Schenck and Lehotay 2000), and hence mask the potential effect of matrices 125 on pesticides recovery, which was the aim of our study. 126

Gas Chromatographic determination 127

A gas chromatograph (Hewlett-Packard 5890, Series II) equipped with NPD (Agilent, 128 Wilmington, USA, 19234-90167), split/splitless injector and autosampler was used. 129

The separation of sample components was performed with an Rtx ® -5ms 30m x 130 Communities 1999). Quantification/recovery of the pesticides in the fortified samples 138 was carried out by comparing the detector responses for each of the three independent 139 samples to those measured in a calibration standard, which was injected both before 140 and after each sample. It should be noticed that maintenance application of the system 141 took place at the end of a pesticide analytical "sequence", defined as the total of 142 samples prepared with one fortification level of one analyte in all 18 matrices. Product 143 extracts were analyzed in the same sequence so that the effect of matrix components 144 can be considered similar in the target analysis. Maintenance included changes 145 associated with the injection site and the front part of the chromatography column 146 being connected with the injection site. Specifically, at the end of an analytical 147 sequence, septum and injection liner were replaced and the good operation of the 148 system was evaluated by injecting the used solvent and a standard solution, containing 149 the investigated pesticides. Cutting the front part of the capillary column was decided 150 upon indications (such as peak width/height/tailing and integrated area) from the 151 injections of standard solutions. Furthermore, by the end of each sequence, 2µL of a 152 standard solution (0.1mgkg -1 ) of pesticides mixture in ethyl acetate was injected to 153 evaluate the reliability of column. In general, the performance of the GC column 154 remained satisfactory for approximately 3-4 sequences. 155

Statistical analysis 156

One way analysis of variance (ANOVA) was applied in order to examine the fixed 157 effects of three experimental factors (pesticide standard, fortification level, matrix) in 158 the recovery of pesticides using the general linear models procedures of SPSS. Then 159 least squared means of recoveries in triplicate trials were calculated and significant 160 differences were estimated by post-hoc tests using Tuckey's method. A significant 161 level of 0.05 was used for all statistical analysis. 162 163

Results and Discussion 164

The first part of this experiment includes the estimate of the NPD response in the 165 examined pesticides. Areas in curves, obtained by injections of pesticide standard 166 solutions, were the means of three replicates for each concentration level. All 167 responses correspond to linear equations in the studied range of 0.01-2.5mgkg -1 , as 168 squared correlation coefficients in this model were found to be >0.9847 (R 2 =0.9959; 169 R 2 =0.9933; R 2 =0.9847; R 2 =0.995 for chlorpyrifos, dimethoate, methamidophos and 170 methidathion respectively). 171

The performance of an analytical method is assessed by several criteria. The 172 recoveries of all used pesticides should be in the range 70-110% with relative 173 standard deviations (RSDs) below 20% (European Communities 1999). In this study, 174 in order to estimate the reliability of the used method, recovery trials were conducted 175 at four fortification levels, chosen as representative range of pesticide concentrations 176 found in the majority of different pesticide-matrix combinations. Specifically, every 177 product was fortified with the target pesticide solutions at the level of MRLs 178 established by EU and at fortification levels of 0.2, 0.5 and 1.5mgkg -1 . The results of 179 the recovery tests are presented at Tables II-V. 180 The type of the examined pesticides was found to influence the occurrence of 182 matrix effect (p<0.05), as the recoveries for the same matrix vary with the different 183 pesticides. Among the used pesticides, the highest recoveries and matrix effects were 184 observed to methamidophos and dimethoate, in the majority of product extracts 185 (especially in the lowest fortification levels). Ιt is notable that methamidophos was not 186 detected in the first injections after the maintenance of the GC system (changing the 187 injection liner) and especially in the first samples of analysis sequence. In these cases, 188 the analysis was repeated, as multiple injections of uncleaned matrix extracts were 189 proved to have a potential effect on the NPD response in this analyte in contrast to the 190 non polar ones. Also, it was found that methamidophos recoveries were of poorer 191 precision in the three repeated injections, as it can be observed from RSDs presented 192 at Table IV. Our findings are in agreement with those of [START_REF] Cai | Rapid multiresidue screening method for 348 organophosphate pesticides in vegetables[END_REF], while 193 similar behavior has been reported for captan and other polar analytes (Hajšlová et al. 194 1998). In contrast to methamidophos and dimethoate, the lowest recovery portions 195 were observed to the non polar analytes chlorpyrifos and methidathion. However, the 196 only cases where matrix effect was observed in those analytes were: pepper in 197 fortification level 0.2mgkg -1 and strawberries (MRL) for methidathion and cucumber 198 (MRL) for chlorpyrifos (Tables II andV). These results are in agreement with Erney 199 et al. (1993), who supported that changes in the recovery portion vary with the 200 chemical structure of the pesticide and those compounds containing P=O bonds, like 201 methamidophos, were identified as tending to give particularly high recoveries. polarity of these bonds. Moreover, as it can be deduced from Table 1 regarding the 206 physicochemical properties (especially values of w.s. and logk ow , which are a degree 207 of polarity), methamidophos and dimethoate are more polar than the other two and for 208 this reason their recoveries are higher, which agrees with the statement of Hajšlová et 209 al. (1998) that the probability of the matrix effect occurrence is higher for more polar 210

pesticides. 211

The ratio of analyte and matrix concentration (fortification level) seems to be a 212 crucial point in the appearance of matrix effect, since there are differences in the 213 recovery portions between the fortification levels for the same pesticides (p<0.05). 214

From the results presented in Tables II-V, it can be proved that the lower is the 215 fortification level the recovery portion is higher. The phenomenon is more evident in 216 the MRLs of 0.02mgkg -1 and especially for the pesticide standard dimethoate in 217 almost all the examined matrices (Table III). This is similar to Hajšlová et al. (1998) 218 and [START_REF] Anastassiades | Evaluation of analyte protectants 345 to improve gas chromatographic analysis of pesticides[END_REF], who noticed unacceptable recoveries and matrix 219 enhancement effects at lower concentration levels of target pesticides and/or at higher 220 matrix components. This behavior can be attributed to the lower competitive effect of 221 the pesticide standards, when they are found in trace fortification levels, for covering 222 the active sites in the injection liner [START_REF] Hajšlová | Matrix effects in (ultra)trace analysis of pesticide 376 residues in food and biotic matrices[END_REF]. 223 It was also observed that in the analysis of some matrices fortified with 224 dimethoate, methamidophos and methidathion at the MRL level, the analytes were 225 under the limit of determination, whereas in the case of other commodities fortified at 226 the same level, the analyte showed an evident peak. Specifically, dimethoate was 227 determined at the level of MRL in all matrices, apart from apricot and peach extracts. 228

Almost the same performance was obtained with methamidophos, where chicory, 229 pepper, kiwi and grapes fortified extracts gave no integrated peaks, at the MRL level 230 of 0.01mgkg -1 . In samples fortified with methidathion in the level of 0.02mgkg -1 , the 231 analyte was detected only in the strawberry extract, contrary to other examined 232 matrices, as cherry, chicory, lettuce, spinach and kiwi fruit, fortified in the same level 233 of MRL. Consequently, the determination of the analyte, at the same trace level in 234 different matrices, is probably influenced by the type of the matrix. This performance 235 was not followed by chlorpyrifos, whose MRL levels are comparatively higher and all 236 peaks were easily integrated. 237

Recovery portion of pesticides also depends on the chemical composition of the 238 matrix (p<0.05). It was found that the type of co-extracts that remains in the final 239 sample leads markedly to different detector response. As a consequence, the botanical 240 categories examined in the experiment can be classified according to the mean 241 recovery portions of the used pesticides (especially in the three fortification levels) in 242 the order: fruiting vegetables and table grapes>strawberries and leafy 243 vegetables>stone fruits and kiwi fruits>pome fruits and citrus. It seems that the 244 highest recoveries were observed to samples containing more non volatile compounds 245 (such as chlorophylls in leafy vegetables, carotenoids in fruiting vegetables, waxes in 246 grapes, lipids in strawberries) compared to samples with more volatile compounds. 247 Thus, higher recoveries are possibly associated with the entrapment of non volatile 248 compounds in the injection liner which are able to cover active sites in the injection 249 liner and/or the front of analytical column and may conduct to higher recoveries. The 250 scientific evidence suggests that more distinct matrix effects have been reported for 251 extracts derived from matrices rich in pigments and lipids [START_REF] Hajšlová | Matrix -induced effects: a critical point in the gas chromatographic 374 analysis of pesticide residues[END_REF]252 Godula et al. 1999;[START_REF] Anastassiades | Evaluation of analyte protectants 345 to improve gas chromatographic analysis of pesticides[END_REF]. Also, when co-extracts, like those 253 mentioned, are accumulated in the inlet, they can create new active sites, intensifying 254 the presence of the phenomenon [START_REF] Anastassiades | Evaluation of analyte protectants 345 to improve gas chromatographic analysis of pesticides[END_REF]. 255 Furthermore, from Tables II-V, it can be revealed that there is no correlation 256 between the classification of plant produce by botanical characteristics and the 257 recoveries of pesticides in the respective extracts, since product extracts belonging to 258 the same botanical category present differences in the pesticides recovery. This 259 statement is more evident especially in the categories of pome fruits, in which quince 260 extracts gave extremely low recoveries in contrast with apple and pear extracts 261 (Tables II-V). Similarly in the citrus category, lemon extracts gave much higher 262 recoveries in contrast with mandarin and orange extracts (p<0.05) (Tables II-V). On 263 the contrary, the three examined products belonging to stone fruits and leafy 264 vegetables present smaller variations, while those belonging to fruiting vegetables 265 present unvarying behavior in the recovery portion of pesticides (p>0.05). 266

In the present study, there are dramatically low recoveries in pesticides in orange 267 extracts, fact opposed to other studies using ethyl acetate as the extraction solvent and 268 clean-up step [START_REF] Dorea | Determination of organophosphorus 354 pesticide residues in fruits by gas chromatography with ITD and NPD detection[END_REF][START_REF] Hajšlová | Matrix -induced effects: a critical point in the gas chromatographic 374 analysis of pesticide residues[END_REF]. Even after the required 269 conditioning of the GC system and three months later, the analysis of the specific lot 270 (frozen oranges), with an independent extract preparation in triplicates, gave the same 271 results. On the contrary, a new lot of oranges from organic produce, analyzed by the 272 same method, gave much higher recoveries in similar combinations of pesticides and 273 fortification levels (results not shown) and the difference was more pronounce in the 274 more polar methamidophos and dimethoate at the fortification level of 1mgkg -1 . 275

Probably, this behavior may be attributed to the specific lot and its different chemical 276 composition, depending on harvest time. 277 Also, it is remarkable that recoveries of pesticides in quince extracts are extremely 278 low in every pesticide and fortification level in comparison with every plant product 279 extract. The existing evidence cannot help to explain this performance, as there are no 280 contain large quantities of water-soluble pectins and the used lot was consisted of 282 immature fruits, which contained higher amounts of pectins, may be the cause of this 283 curious behavior, as it is presumed that these ingredients detain important quantities 284 of active ingredients in the extraction step. 285

Moreover, it should be noted that most matrices generally gave chromatograms 286 free of peaks in the blank extracts. Nevertheless, especially in the cases of leafy 287 vegetables and citrus extracts there were found some peaks in different retention times 288 of both the examined pesticides in this study and other organophosphorus pesticide 289 standards analyzed in our laboratory. These may be lipophilic compounds derived 290 from those matrices not removed by the extraction method, as there has been observed 291 similar behavior in uncleaned sample extracts in ethyl acetate [START_REF] Cai | Rapid multiresidue screening method for 348 organophosphate pesticides in vegetables[END_REF]292 Maštovská and Lehotay 2004). The fact that the same peak in orange extracts 293 appeared in every orange, either of organic produce or of conventional crop, and 294 detected in the peel orange extract analyzed itself compared to the analysis of orange 295 juice, may be the reason why some citrus peels require clean-up step, described by 296 [START_REF] Dorea | Determination of organophosphorus 354 pesticide residues in fruits by gas chromatography with ITD and NPD detection[END_REF]. 297

Finally, it should be addressed that matrix enhancement effect is difficult to study 298 because the GC system changes as matrix components are progressively deposited in 299 the injection port and front of the analytical column (Schenck and Lehotay 2000). 300

Moreover, the injection technique has been found to play a major role on the 301 occurrence of matrix effect. Specifically, the use of cold on-column injection is 302 considered as one of the most practical approaches by which, pesticides thermolysis 303 and decomposition or adsorption inside the inlet could be avoided [START_REF] Wylie | Improved gas chromatographic analysis of organophosphorus 398 pesticides with pulsed splitless injection[END_REF]304 Godula et al. 1999). With the specific technique, more accurate results have been 305 observed, especially for troublesome analytes, compared to splitless injection as long 306 as the chromatography system remains clean [START_REF] Wylie | Improved gas chromatographic analysis of organophosphorus 398 pesticides with pulsed splitless injection[END_REF]. Furthermore, it is likely volatile compounds, could be analyzed by on-column injection with the parallel use of 309 a packed column or a deactivated precolumn (to keep most of the remaining matrix 310 constituents of the extract) connected to the injector site. However, the disadvantage 311 of on-column injection is that it seems to be impractical for applications of complex 312 or relatively uncleaned matrices, because it requires more maintenance of the column 313 and thus, hot splitless injection tends to be preferrable [START_REF] Anastassiades | Evaluation of analyte protectants 345 to improve gas chromatographic analysis of pesticides[END_REF]. The 314 effect of maintenance application by changing the injection liner and/or the column is 315 also unpredictable, because as Godula et al. (1998) indicated, the history of the GC 316 system (especially changes in the injection port) plays an important role in the 317 occurrence of matrix effects. Consequently, recoveries of pesticides are not 318 reproductable and the effects of co-extracts can not be considered as stable and 319 foreseeable. For these reasons, it is better to provide recovery data and validate the 320 used method in only one produce, especially when the product is suspected for matrix 321 effects, so that the existence of matrix effect can be checked rather than providing 322 recoveries in one produce and validate the method in the whole botanical category. 323

In conclusion, the results of the present study indicate that higher pesticide 324 recoveries should be expected at more polar analytes, fortified at low concentrations 325 in matrices rich in non volatile compounds. Moreover, different recoveries may occur 326 among products of the same botanical group. Therefore, examining the recoveries of 327 target pesticides, using an official method, in only one representative plant product 328 with the purpose of validating the method for the whole botanical category is possibly 329 an erroneous practice. Indeed, the combined outcome of factors, such as analytes, 330 matrix, and fortification level on the pesticide recovery can not always be predicted. 331

The above suggest that validation of an official method for the analysis of pesticide 332 residues should not be based only on the botanical categories of plant products. Such 333 practice may be useful, for the simplification of issuing validation, when matrix-334 matched calibration standards and/or extensive clean-up of the samples are used prior 335 to the final chromatographic step. Conversely, the same practice is insuffient for 336 quantification with standards in neat solvent and/or in the final extract without 337 additional clean-up step. However, in order to further examine the analytical 338 performance of different product extracts, a matrix-matched calibration procedure for 339 each product should be severally carried out. Furthermore, the analysis of each group 340 of commodities fortified in many more levels, with a higher number of pesticides is 341 strongly recommended and may possibly explicate the differences between the 342 recovery portions of products of the same category that the current study brought out. 343 107.0 ± 3.6 ab 157.9 ±14.8 (0.02) 137.9 ± 5.4 (0.02) 165.5 ±12.9 (0.02)

F

Various

• Kiwi fruits 107.0 ± 3.6 ab 157.9 ±14.8 (0.02) 137.9 ± 5.4 (0.02) 165.5 ±12.9 (0.02)

Various

• Kiwi fruits

  were obtained from a local market for organic 102 farming produce. Particularly, pome fruits (pears, apples and quinces), citrus (lemons, 103 mandarins and oranges), stone fruits (apricots, cherries and peaches), fruiting 104 vegetables (cucumbers, tomatoes and peppers), leafy vegetables (lettuce, spinach and 105 three other products not belonging to a specific group (kiwi fruits, table106

  id x 0.25µm film thickness (Restek, USA, 12624) capillary column. The 131 injection port temperature was 260 o C and the detector temperature 300 o C. The oven 132 temperature was programmed as follows: initial temperature 70 o C for 1min, raised at 133 15 o Cmin -1 to 130 o C for 0min, raised at 5 o Cmin -1 to 230 o C and finally raised at 134 20 o Cmin -1 to 250 o C with a residence time of 13min. Helium carrier gas at flow rate of 135 8mLmin -1 was used. Triplicate extracts (2µL) were injected and quantification of the 136 insecticides was performed by automatic integration of the peak areas (European 137

  202Schenck andLehotay (2000) noticed that compounds with P=O bonds tend to exhibit 203 more matrix effects rather than those with P=S bonds, like the one present in the 204 molecule of dimethoate, chlorpyrifos and methidathion, because of the highest 205

  data derived from quince extracts. The fact that quinces 281

Recovery

  c: means within a plant product category and fortification level lacking a 411 common superscript letter are different (p<0.05). 412 Bold letters designate recoveries within the acceptable range of recovery (70-110%). 418 Values in parenthesis indicate the levels of MRLs established by EU. 419

Recovery

  Bold letters designate recoveries within the acceptable range of recovery (70-110%). 9Values in parenthesis indicate the levels of MRLs established by EU. 10

Recovery

  c: means within a plant product category and fortification level lacking a 11 common superscript letter are different (p<0.05). 12 Bold letters designate recoveries within the acceptable range of recovery (70-110%). 18 Values in parenthesis indicate the levels of MRLs established by EU. 19

Recovery

  c: means within a plant product category and fortification level lacking a 29 common superscript letter are different (p<0.05). 30 Percentage recoveries and RSDs of methidathion in the different plant 34 products, classified by botanical characteristics, and in different fortification levels. 35 Bold letters designate recoveries within the acceptable range of recovery (70-110%). 36 Values in parenthesis indicate the levels of MRLs established by EU. 37

  c: means within a plant product category and fortification level lacking a 38 common superscript letter are different (p<0.05). 39

Table II .

 II Percentage recoveries and RSDs of chlorpyrifos in the different plant 407 products, classified by botanical characteristics, and in different fortification levels. 408 Bold letters designate recoveries within the acceptable range of recovery (70-110%). 409 Values in parenthesis indicate the levels of MRLs established by EU. 410

		o r F o r Pesticide (Retention time) w.s. (mgL -1 ) Chlorpyrifos (24.6 min) 1.4 Plant products 1.5mgkg -1 Pome fruits during open tubular column gas chromatography with splitless or hot on -column F logk ow M.p. ( o C) V.p. (mPa) 4.7 42-43.5 2.7 Recovery ± RSD (%) 0.5mgkg -1 0.2mg/kg -1 MRL (mgkg -1 )* o r F o r Dimethoate (18.9 min) 24000 0.7 43-45 0.25 Methamidophos 200000 -0.8 45 2.3 r o • Pear F • Apple
		(8.9 min)	P P P P P
	402	Methidathion (27.1 min)	e e r e e r e e r e e r 200 e e r	2.2	39-40	0.25
	403	w.s.: water solubility (20 o C)	R R R R R
	404 405 406	e v i e w e v i e w e v i e w e v i e w logk ow : log of n -octanol partition coefficient e M.p.: melting point. V.p.: vapour pressure (25 o C). v i e w
						O n l O n l O n l O n l O n l
							y y y y y

Table I .

 I Bold letters designate recoveries within the acceptable range of recovery (70-110%). 427 Values in parenthesis indicate the levels of MRLs established by EU. 428 Bold letters designate recoveries within the acceptable range of recovery (70-110%). 436 Values in parenthesis indicate the levels of MRLs established by EU. 437 Physicochemical properties of the target pesticides. 1

		Pesticide
			w.s. (mgL -1 )	logk ow	M.p. ( o C) V.p. (mPa)
		(Retention time)
		Chlorpyrifos
				1.4	4.7		42-43.5	2.7
		Plant products Plant products (24.6 min)		1.5mgkg -1 1.5mgkg -1	Recovery ± RSD (%) 0.5mgkg -1 0.2mgkg -1 Recovery ± RSD (%) 0.5mgkg -1 0.2mgkg -1	MRL (mgkg -1 )* MRL (mgkg -1 )*
		F o r F o r Pome fruits • Pear • Apple • Quince F o r F o r Pome fruits • Pear • Apple • Quince F o r Dimethoate F (18.9 min) o Methamidophos r	82.3 ± 4.8 b 77.7 ± 5.0 b 32.0 ± 4.7 a 69.8 ± 1.4 b 81.9 ± 2.9 c 40.5 ± 0.8 a 24000 200000	82.2 ± 2.9 b 93.2 ± 11.2 b 20.2 ± 1.8 a 62.1 ± 3.1 b 77.2 ± 2.8 c 40.2 ± 2.2 a 0.7 -0.8	111.8 ± 2.6 b 106.3 ± 17.8 b 38.3 ± 10.0 a 74.4 ± 1.6 b 90.8 ± 1.0 c 46.0 ± 1.7 a 43-45 0.25 45 2.3	99.6 ± 5.8 (0.05) Not detected (0.05) 88.9 ± 6.0 (0.05) 74.2 ± 7.2 (0.3) 88.8 ± 1.9 (0.3) 73.6 ± 10.8 (0.3)
	2	Citrus • Lemon • Mandarin • Orange Stone fruits Citrus • Lemon • Mandarin • Orange (8.9 min) Stone fruits Methidathion (27.1 min)	P e e r P e e r 103.6 ± 7.7 b 69.1 ± 1.9 a 58.2 ± 9.3 a P e e r P e e r 79.7 ± 0.3 c 59.1 ± 2.8 a 44.4 ± 0.8 b P P e e r e 200 e r	114.8 ± 3.8 b 78.8 ± 6.9 a 63.8 ± 6.6 a 86.1 ± 1.6 b 40.7 ± 0.4 a 37.6 ± 5.4 a 2.2		105.8 ± 5.6 c 73.2 ± 6.8 b 56.8 ± 4.3 a 73.0 ± 6.4 b 44.6 ± 13.1 a 44.8 ± 14.2 a 39-40 0.25	105.8 ± 5.6 (0.2) 73.2 ± 6.8 (0.2) 56.8 ± 4.3 (0.2) 81.9 ± 8.7 (2.0) 61.2 ± 5.1 (2.0) 53.2 ± 4.5 (2.0)
	3	R e v i e w R e v i e w 88.0 ± 12.0 a 70.9 ± 9.5 a 78.8 ± 1.4 a 120.6 ± 6.3 b 79.9 ± 7.3 a 83.4 ± 1.6 a 100.0 ± 14.8 a 88.5 ± 3.7 a 87.7 ± 8.9 a 108.8 ± 2.3 b 72.4 ± 3.8 a 98.8 ± 9.4 b 97.7 ± 1.5 a 119.3 ± 2.8 b 117.9 ± 2.5 b 97.9 ± 1.3 a 110.4 ± 4.6 a 128.4 ± 15.6 a R e v i e w R e v i e w 70.9 ± 2.5 a 76.0 ± 2.2 a 68.3 ± 2.0 a 85.9 ± 2.8 b 87.9 ± 2.2 b 59.8 ± 3.4 a 100.9 ± 4.2 b 90.5 ± 10.4 b 60.0 ± 17.7 a 60.3 ± 2.1 a 73.9 ± 4.5 b 53.9 ± 1.3 a 70.9 ± 0.7 a 76.2 ± 2.4 b 68.2 ± 1.6 a 76.5 ± 13.7 a 71.0 ± 9.4 a 73.9 ± 8.6 a w w v i e e i v e e R R w.s.: water solubility (20 o C) • Apricot • Cherry • Peach Leafy vegetables • Lettuce • Chicory • Spinach • Apricot • Cherry • Peach Leafy vegetables • Lettuce • Chicory • Spinach	120.0 ± 4.3 (0.1) 166.0 ±15.0 (0.01) Not detected (0.05) 97.9 ± 1.3 (0.2) Not detected (0.01) 288.4 ± 2.7 (0.01) 100.9 ± 4.2 (0.2) Not detected (0.02) Not detected (0.02) Not detected (0.02) 60.0 ± 17.7 (0.2) Not detected (0.02)
		Fruiting vegetables • Cucumber • Pepper • Tomato Various Fruiting vegetables • Cucumber • Pepper • Tomato Various		96.7 ± 13.9 a 82.7 ± 2.3 a 98.8 ± 3.8 a 84.8 ± 3.4 b 72.0 ± 4.1 a 97.1 ± 4.8 c	98.8 ± 3.9 a 96.2 ± 0.9 a 96.8 ± 0.8 a 106.4 ± 4.9 a 102.3 ± 2.8 a 93.9 ± 4.0 a	O n l y O n l y 102.1 ± 2.2 a 108.2 ± 6.4 a 95.2 ± 16.8 a O n l y O n l y 104.5 ± 3.4 a 112.2 ± 0.5 a 109.5 ± 1.3 a O n l O n l y y	107.5 ± 8.2 (1.0) Not detected (0.01) Not detected (0.05) Not detected (0.02) Not detected (0.02) 109.5 ± 1.3 (0.2)
		• Kiwi fruits • Kiwi fruits		80.2 ± 2.0 87.9 ± 7.1 58.7 ± 3.4	85.1 ± 3.7 75.7 ± 6.7 53.5 ± 4.1		87.4 ± 9.3 92.8 ± 8.7 76.6 ± 3.7	141.9 ± 8.5 (0.02) Not detected (0.01) Not detected (0.02)
		• Table grapes • Table grapes • Table grapes		92.9 ± 1.8 76.8 ± 4.7 91.8 ± 2.8	87.0 ± 6.4 90.0 ± 4.1 98.0 ± 2.8		89.0 ± 3.3 91.0 ± 5.4 98.0 ± 4.6	150.0 ±13.5 (0.02) Not detected (0.01) 98.0 ± 2.8 (0.5)
		• Strawberries • Strawberries • Strawberries	89.5 ± 0.3 102.2 ±1.2 60.5 ± 1.6	111.6 ± 0.6 108.0 ± 5.2 86.4 ± 2.1		135.4 ± 3.2 103.4 ± 12.3 81.4 ± 5.0	146.3 ± 7.3 (0.02) 210.4 ± 3.5 (0.01) 292.6 ± 8.9 (0.02)
	420 429 438	a, b, c: means within a plant product category and fortification level lacking a a, b, c: means within a plant product category and fortification level lacking a a, b, c: means within a plant product category and fortification level lacking a
	421 430 439	common superscript letter are different (p<0.05). common superscript letter are different (p<0.05). common superscript letter are different (p<0.05).

  Values in parenthesis indicate the levels of MRLs established by EU. 28

		Plant products		1.5mgkg -1	Recovery ± RSD (%) 0.5mgkg -1 0.2mgkg -1	MRL (mgkg -1 )*
		F o r Pome fruits F • Pear o • Apple r • Quince	82.3 ± 4.8 b 77.7 ± 5.0 b 32.0 ± 4.7 a	82.2 ± 2.9 b 93.2 ± 11.2 b 20.2 ± 1.8 a	111.8 ± 2.6 b 106.3 ± 17.8 b 38.3 ± 10.0 a	99.6 ± 5.8 (0.05) Not detected (0.05) 88.9 ± 6.0 (0.05)
		Citrus • Lemon • Mandarin • Orange	P e e r P 103.6 ± 7.7 b e 69.1 ± 1.9 a e r 58.2 ± 9.3 a	114.8 ± 3.8 b 78.8 ± 6.9 a 63.8 ± 6.6 a	105.8 ± 5.6 c 73.2 ± 6.8 b 56.8 ± 4.3 a	105.8 ± 5.6 (0.2) 73.2 ± 6.8 (0.2) 56.8 ± 4.3 (0.2)
				R R
				e e
					v i e v i e
					w w
						O n l O n l
						y y
				80.2 ± 2.0	85.1 ± 3.7	87.4 ± 9.3	141.9 ± 8.5 (0.02)
		• Table grapes		92.9 ± 1.8	87.0 ± 6.4	89.0 ± 3.3	150.0 ±13.5 (0.02)
		• Strawberries		89.5 ± 0.3	111.6 ± 0.6	135.4 ± 3.2	146.3 ± 7.3 (0.02)
	20	a, b, c: means within a plant product category and fortification level lacking a
	21	common superscript letter are different (p<0.05).

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

that polar analytes, such as methamidophos, and matrices, containing especially non

injection and flame photometric detection. Journal of Chromatography 638:57-63.

Godula M, Hajšlová J, Alterova K. 1999. Pulsed splitless injection and the extend of

enhancement effect in gas chromatographic analysis of pesticide residues in food?

Journal of Chromatography A 868:51-61.

0.5mgkg -1 ). For this reason the respective recoveries appear in two columns of the

products, classified by botanical characteristics, and in different fortification levels.