Ioannis V Zioris

Theoharis Dimitra G Lambropoulou

George Danis

Dr Dimitra T Karagiozogloy

Triantafyllos Albanis
email: talbanis@uoi.gr

Despoina T Karagiozoglou

Assessment of Pesticide Residues in Fresh Peach Samples Produced Under Integrated Crop Management in a Greek Agricultural Region on the North Greece

Keywords: Peaches, analysis, pesticides, gas chromatography-mass spectrometry 36 ), integrated crop management (ICM) Chlorpyriphos-methyl, Phosmet, Tebuconazole, Penconazole, Myclobutanil, Propargite, Amitraz, Diazinon, Deltamethrin, Indoxacarb, Malathion, Dimethoate, Phosalone, Fenthion, Methamidophos,

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

programmed in SIM using one target and two qualifier ions, as indicated in Table 1.

151

Groupings were defined to increase the sensitivity of the MS analysis. The injection 152 volume was 1 µL for all standards and samples.

153

Quality control.

154

Identification and confirmation of the target compounds was based on the quality 155 control procedures established by the EU [START_REF] Soler | Liquid chromatography-electrospray quadrupole ion-473 trap mass spectrometry of nine pesticides in fruits[END_REF]). Thus, identifications of 156 pesticides in peach samples were made by comparing the retention time, identifying 157 the target and qualifier ions, and determining the qualifier-to-target ratios of the peak 158 in the peaches with that of a pesticide standard. Acceptance criteria for positive 159 identification consisted of retention times within (0.50 min of the expected) value and 160 % qualifier-to-target ratios within 20% of the standard (0.1 mg L -1 ) for qualifier-to-161 target abundance percentages greater than 50%. For less than 50%, the criterion for Linearity was established by performing calibration sets at concentrations of 0.25, 0.5, 196 0.75, 1.0, 2.5, 5 and 10 µg ml -1 (corresponding to 0.25 -10 ng on-column and 0.005-197 0.5 mg kg -1 in the sample), both in solvent and in matrix. To exclude memory effects, 198 the first series of data, obtained starting from a lower concentration, was compared 199 with the second, obtained starting from a higher concentration, for a total of four 200 replications for each point. The calibration curves were constructed by applying the 201 least-squares method and using the equation y = mx + q as the regression model.

202

For solvent standards the regression coefficients for all 23 target compounds 203 were above 0.9900. In the presence of peach matrix, excellent linearity was still 204 obtained for the majority of the target compounds except for captan, methamidophos 205 and indoxocarb the correlation coefficients of which were below 0.990. From these 206 results it can be concluded that the GC-MS system is suitable for quantitative 207 measurement of the target pesticides in peach matrices.

208

Precision of Method.

209

The overall method accuracy and precision was conducted following the EU criteria ). At each level, the analysis was performed with six 213 replicates. The same protocol was applied for performance data under intermediate 214 reproducibility conditions but analyses (i.e., six blank peaches spiked at each of the 215 two fortification levels) were conducted by two analysts over a 1-month period. Table 216 2 summarizes these data. The results of intraday precision are showed in Table 2 near 217 recovery data, while those of inter-day variability, for the three peach matrices spiked 218 at 100 µg kg _1 , are listed in Table 1. Within-and between-day, as well as within-219 laboratory, precisions were below 18%. Precisions at fortification level at 500 µg kg -1 220 were better and below 12%. In this study captan, showed low recoveries (<70%) in peach samples, which 265 was probably related to the sample matrix, which somehow did not fit well with the 266 chosen solvent. In addition lower recoveries are mostly linked to pesticides that may 267 not be stable or decompose during sample preparation, and GC injection. Captan is a 268 well-known problematic pesticide in multi-residue analyses being difficult to 269 determine using existing methods and recoveries lower than 70% have been also 270 reported in other studies ((Lehotay et al., 2005[START_REF] Pihlström | Analysis of 461 pesticide residues in fruit and vegetables with ethyl acetate extraction using gas 462 and liquid chromatography with tandem mass spectrometric detection 463[END_REF], Hercegová et 271 al., 2007). This example illustrates the difficulties to development a unique procedure

272

for the extraction of a wide range of pesticides with different physical properties (i.e.: 273 polarity and/or solubility). Although the recoveries of this compound were less than 274 the guideline value, it is worth to say that they were nevertheless consistent as 275 observed from their standard deviations at any of the fortification levels (Table 2).

276

There was no significant difference in recoveries among sample types or 277 spiking levels. Average recoveries of 23 pesticides in 18 samples were around 90%.

278

Most chromatograms were clear enough to identify and determine each pesticide with 279 primary ion detection. These results demonstrate the feasibility of the studied 280 extraction method.

281

The similarity in recoveries obtained for a given pesticide in the three peach When a MS detector is used, the first condition to be satisfied for ascertaining the 287 presence of a target compound is that the precursor ion and at least two product ions 288 produce signals distinguishable from the background ion current. Accordingly, a 289 definition of LOD (S/N 3) of each analyte was adopted, considering in each case the 290 ion giving the worst S/N. When more than three ions were selected for analyte 291 identification (see Table 1), LODs were estimated by selecting signals for the parent 292 ion and, among fragment ions, the two giving the best S/N. The background noise 293 estimate was based on the peak-to-peak baseline near the analyte peak. The noise 294 level depends on the matrix; therefore, there are different LODs for different samples.

295

In reference to this, LODs were estimated from the SIM chromatogram referring to 296 the analysis of 50 µg kg -1 of each analyte in peach, of several peach matrices. LOQs, 297 according to the EU guidelines were defined as lowest concentration that provided 298 acceptable recoveries and RSDs (<19%) (Anastassiades et al. 2003). The LOQs of 299 this method are well below the MRLs set by the EU and FDA for residues of 300 pesticides in food matrices.

301

Specificity.

302

Six repetitive analyses showed excellent similarities with reference to the retention 303 time for all pesticides (between 95% and 100%). Additionally, the similarity of ethyl 304 bromophos as the internal standard was over 99%, indicating that the analytical 305 procedure and the chromatographic column yielded consistent and specific results.

306

Monitoring studies.

307

The proposed procedure was applied to the analysis of 104 peach samples taken from

319

The total results from the peach samples analyzed are summarized in Table 3. 4. 324 Among the 23 pesticides included in the present monitoring study only 10 of 325 them were finally detected in the peach samples. The detected pesticides were 326 chlorpyriphos, tebuconazole, chlorothalonil, phosmet, captan, malathion, diazinon, 327 bifethrin, propargite and indoxacarb, which are the most widespread-used pesticides 328 in the peaches crops in the Imathia region (Fytianos et al. 2006;[START_REF] Tsakiris | Monitoring of pesticide residues in fresh peaches produced 477 under conventional and integrated crop management cultivation[END_REF]).

329

The results showed an occurrence of these pesticides in a range of 1% to 46% 330 depending on the compound and the sampling station. Montemurro et al. 2002). It is worth saying that, statistically significant higher levels 339 of chlorpyriphos residues in peach samples from early varieties were observed 340 compared with the samples of late varieties. From this result a question arises 341 regarding the fate of this compound in the environment. To the best of our knowledge 342 the fate of this pesticide under natural environmental conditions is not thoroughly 343 investigated and thus future work will be needed to study its degradation and 344 transformation, especially under local climatic condition, for the further 345 understanding of its persistence in the food commodities.

346

Captan was detected in higher concentrations than the other pesticides and in 347 almost all the sampling places (Figure 1). However, in all cases the concentration was 348 lower than the MRL levels and ranged between 0.04 and 0.14 mg kg -1 . Chlorothalonil 349 was detected in five different samples and only in three from the four sampling 350 stations at low concentration levels (mean concentration 0.03 mg kg -1 ). It is worth 351 noting that, although diazinon was found and quantified in only five different 352 samples, it had an average concentration equal or even higher (one sample) to the EU 353 MRL in all cases. This result clearly indicates that more monitoring studies and proof 354 is needed to assess if this compound can possess potential risk for the consumers' 355 health.

356

The other detected pesticides (tebuconazole, bifethrin, phosmet) had an 357 occurrence in the peaches that did not exceed 23%. The concentration levels ranged 358 between 0.01 and 0.06 mg kg -1 depending on the pesticide and the sampling station.

  specific cultivation by the Greek Ministry of Agriculture. Presently, 90 14 acaricides, 65 insecticides, 9 herbicides and 43 fungicides (total of 131 pesticides) 91 are registered in Greece (Gianopolitis 2006). The reported number of crop protection 92 products, i.e. 131, represents the total number of pesticide formulations that might 93 contain the same active ingredient. In terms of the active ingredients, the 23 chemicals 94 selected for testing represent all the residues likely to be present in peaches (Tsakiris 95 et al. 2004). 96 Monitoring was performed for the following most frequently used categories 97 of crop protection products: 98 • Insecticides: Methamidophos, Dimethoate, Chlorpyriphos-methyl, Parathion-99 methyl, Malathion, Chlorpyriphos, Fenthion, Ethion, Phosalone, Diazinon, 100 Methidathion, Bifethrin, Phosmet, Indoxacarb, Deltamethrin. 101 • Fungicides: Chlorothalonil, Captan, Penconazole, Myclobutanil, Tebuconazole. 102 • Acaricides: Dicofol. Propargite, Amitraz. 103 All classes are of interest because of their extensive use or potential adverse 104 health effects. 105 Fresh Peaches Sampling. 106 Fresh peaches were collected from four selected fields at the banks of Aliakmonas 107 River in Imathia region, during the cultivation period of 2006 and were of various 108 species. 104 samples were collected all under IPM production. All fruits had reached 109 their final size. Samples were collected as indicated in Directive 79/700/EEC 110 (Commission Directive 79/700/EEC 1979), which stipulates the European Union 111 methods of sampling for the official control of pesticide residues in and on products 112 . After dehydration (with sodium sulfate) and concentration (under a gentle 138 nitrogen stream at a constant 37 o C), the sample was transferred to a pre-conditioned 139 (5 ml acetonitrile: toluene, 3:1) ENVI-Carb SPE tube and eluted with a 10-ml mixture 140 of acetonitrile: toluene (3:1). The sample was evaporated almost to dryness and 141 reconstituted with 0.5 ml acetonitrile, which was analyzed by GC. 142 GC-MS analysis. 143 A Shimadzu (Kyoto, Japan) QP 5050A GC-MS was used with an MDN-5S fused 144 silica capillary column 30m x 0.32mmi.d. (Supelco). Helium was used as the carrier 145 gas at 87.5 kPa and 1.5 ml min -1 flow rate. The injection temperature was 220 o C. The 146 column was programmed from 50 to 160 o C (10 min) at 5 o C min -1 (first step) and 147 from 160 to 250 o C (20 min) at 15 o C min -1 (final step). The interface was programmed 148 at 250 o C. Electron ionization was used with a detector voltage of 1.2 kV, mass range 149 from 45 to 400 m/z, and scan speed of 1000 amu s -1 . The MS system was routinely 150

  to-target ratios was set at 30% of the calibration standard. Fruit blanks 163 and spikes were analyzed to account for any residual carry over or possible 164 contamination sources such as the glassware. The identification of pesticide residues 165 in the blanks resulted in repeating the extraction and analysis of the entire batch. 166 Quantification of peach extracts. 167 In order to avoid quantitative errors, matrix-matched standards were used in this 168 study. The homogenized samples were subsequently used as blanks and in the 169 preparation of matrix-matched standards for calibration. Matrix-matched calibration 170 standards were prepared by adding known quantities of standard mixture solutions to 171 the corresponding blank sample extracts. Matrix-matched standards at concentration 172 levels ranging from 0.25 to 10 µg ml -1 were prepared by dilution of mixture-standard 173 solutions in peach final extracts prepared from unfortified samples. The internal 174 standard was added to all calibration standard solutions. Two types of peaches 175 (freestones and clingstones) and nectarines were chosen for recovery and 176 reproducibility studies. Fresh clingstone peaches were collected from a field near the 177 town of city of Veria in the middle of the harvesting period (29 August 2006). The 178 mean recoveries of selected pesticides, three replications per level and RSDr are 179 presented in Table 2. 180 Spiking procedure. 181 For spiking studies, a measured 25 g test portion of peach sample with no pesticides 182 detected previously was spiked with appropriate standard solutions to a final 183 concentration of 0.05, 0.10 and 0.50 mg kg -1 , and the Teflon centrifuge tube was 184 vigorously vortexed to distribute the pesticide residues. The same procedure described 185 in extraction procedures was applied to the spiked samples.

  The analytical performance of the proposed method was studied in order to evaluate 190 its usefulness for quantitative analyses in the studied matrices. The accuracy (as 191 recovery), linearity, precision [as repeatability (RSD r ) and reproducibility (RSD R )], 192 matrix effect, limits of detection (LODs) and limits of quantifications (LOQs) were 193 established to validate the procedure. 194 Linearity.

  195

  210 for validation of pesticide residue methods (SANCO/10476/2003 2003; 211 SANCO/3131/2007 2007) by analyzing fortified clingstone peach samples at three 212 100 and 500 µg kg -1

222

  In food analysis by mass spectrometry, signal suppressions may occur during the 223 ionization process of the extracts due to the composition (salts, proteins, lipids, 224 carbohydrates etc) of the matrix under survey. This matrix effect can be minimized by 225 an efficient cleanup of the extract, but usually cannot be totally avoided. In a recent 226 comprehensive review (Hajšlova and Zrostlíková 2003) the nature of various types of 227 matrix effects was discussed together with suggestions for prevention, reduction 228 and/or compensation of their occurrence when determining troublesome analytes in 229 food matrices. In this context, for all the pesticides considered here, including 230 bromophos ethyl candidate for use as internal standard, we conducted a study aimed 231 at assessing variations of the matrix effect (if present).

232

  For this purpose, we checked the matrix effects of different peaches on the 233 analysis of the tested pesticides by constructing matrix-matched calibration curves 234 and comparing their slope with those of calibration curves constructed in solvent.235Table2summarizes these data and shows that in GC/MS, the matrix seemed to be 236 slightly dependent of the particular peach extract analyzed for most of the target 237 pesticides (chlorpyrifos and parathion methyl) the matrix 239 produced either suppression or enhancement with fluctuations of up to about ±30% 240 depending also on both the matrix and each individual species. For this reason, the 241 calibration was carried out using matrix matched standards, in order to improve the 242 accuracy of the analysis of these compounds. 243 Recovery Test. 244 To evaluate the effectiveness of the extraction method, different recovery studies were 245 performed by spiking peach matrices at three spike levels, that is, 50, 100 and 500 µg 246 kg -1 . At each concentration, six measurements were performed. Two different types of 247 peaches (freestone and clingstone) and nectarines were also selected for pesticide 248 fortification studies based on their different properties. The purpose of choosing the 249 three different peach matrices for the pesticide fortification studies was to determine 250 whether the proposed multi-residue method is applicable to different peach matrices 251 regardless of their properties. 252 Freestone types of peaches were chosen for this study because it is 253 representative of a standard peach found commonly in Greek markets. Clingstone 254 type peach was chosen for the study based on its similarity to freestone ones in terms 255 of flavor, and appearance but it is different because of the tightest flesh to the pit. 256 Freestone types are usually preferred for eating fresh or for freezing, while clingstone 257 types are used primarily for canning. The nectarines differ from the other two types of 258 peaches due to its lack of fuzz on the skin. 259 Data are reported inTable 2 which show the 23 pesticides were recovered in 260 the range of 64-104% with 2-18% of relative standard deviation (RSD) at all spiking 261 levels. Thus, for all pesticides (except for captan and bifethrin), average recoveries 262 with criteria that sets acceptable mean recovery to be between 70 and 263 120% with RSD≤20% (SANCO/10476/2003 2003; SANCO/3131/2007 2007) 264

282

  matrices indicates that different fruit characteristics likely to be encountered in real 283 samples would have little impact on method performance and is indicative of the

308

  different local farmers who performed the ICM up to 3 years. Internal quality control 309 was applied in every batch of samples in order to check if the system is under control. 310 This quality control implies a matrix-matched calibration, a reagent blank, a matrix 311 spiked blank sample at 100 µg L -1 in order to evaluate stability of the 312 proposed method with time. 313 With each batch of 10 samples, a five-point calibration curve was prepared for 314 analytes concentrations between the LOQs and 10 LOQs by injections before and 315 after those of the sample extracts. In addition, 2 quality control (QC) samples were 316 injected in every batch of samples. The QC samples were blank peach sample 317 fortified at LOQ level and 10 times the LOQ level. All the samples were injected in 318 duplicate.

320

  Statistical analysis of the quantified residual levels of the detected crop protection 321 products in peach samples from IPM system the number of detected samples, their 322 average concentration and finally the European Maximum Residues Limits are 323 presented in Table

331

  Chlorpyriphos (O,O-diethyl O-3,5,6-trichloro-2-pyridyl phosphorothioate) was 332 the crop protection product most frequently detected in samples collected ICM 333 cultivation systems with an occurrence up to 44.2 % (Figure 1) of the total number of 334 samples (46 positive samples). The concentrations varied between 0.025 to 0.050 mg 335 kg -1 (

359

  Methamidophos was not detected in any samples, thus confirming previous findings 360 the effectiveness and residues level of the active substances in order 387 to modify their plans for the next year cultivation period. Lehotay SJ, Štajnbaher D, Schenk FJ. 2003. Fast and easy 391 multiresidue method employing acetonitrile extraction/partitioning and 392 "dispersive solid-phase extraction" for the determination of pesticide residues in 393 produce. J AOAC Int, 86, 412-431 394 Baker, BP. Benbrook CM., Groth III E, Lutz Benbrook K. 2002. Pesticide residues in 395 conventional, integrated pest management (IPM)-grown and organic foods: 396 insights from three US data sets Food Additives & Contaminants 19 (5), 427-Hajslova J, Lacina O, MastovskaK, Lehotay SJ. 2008. Rapid analysis of 399 multiple pesticide residues in fruit-based baby food using programmed 400 temperature vaporiser injection-low-pressure gas chromatography-high-401 resolution time-of-flight mass spectrometry. Journal of Chromatography A.

Figure 1 Page

 1 Figure 1Rate of detection of pesticides from the total samples of peaches

Table 3 )

 3 , depending on the sampling station. These findings are in agreement

	336

Table 1 .

 1 Target pesticides, , Retention time (t R )*, Target and Qualifier ions (T, Q 1 and Q 2 )*, Percentage of Qualifier -to -Target Ratios, (Q 1 /T

	1
	2	and Q 2 /T)*, LODs*, LOQs*, Regression Coefficient (r 2 )*, matrix effect and inder-day -precision (RSD R )*.
		Pesticides	tR (min)	T	Q1(Q1/T%)	Q2(Q2/T%)	LOD (mg Kg -1 )	LOQ (mg Kg -1 ))	Matrix effect (Slope M/S)	% RSDR (n=6) 100 (µg Kg -1 )
		Methamidophos	18.00	94	141 (53)	79 (36)	0.002	0.005	1.0	13
		Dimethoate	28.27	87	93 (61)	125 (58)	0.005	0.015	0.9	10
		Diazinon	28.77	179	137 (98)	152 (67)	0.001	0.004	1.1	8
		Chlorothalonil	29.08	266	229 (85)	264 (79)	0.002	0.005	0.9	9
		Chlorpyriphos-Methyl	29.81	286	109 (66)	125 (54)	0.001	0.002	1.1	8
		Parathion-Methyl	29.94	263	109 (110)	125 (99)	0.003	0.010	1.3	10
		Malathion	30.45	173	93 (86)	125 (85)	0.003	0.010	1.2	12
		Chlorpyriphos	30.66	97	197 (71)	314 (69)	0.001	0.003	1.3	9
		Fenthion	30.77	278	109 (31)	125 (24)	0.001	0.002	1.1	12
		Dicofol	31.08	139	111 (56)	251 (48)	0.001	0.004	1.0	10
		Penconazole	31.52	248	159 (90)	161 (61)	0.001	0.002	1.0	9
		Captan	31.90	79	107 (21)	117 (12)	0.008	0.025	0.7	18
		Methidathion	32.10	145	85 (61)	93 (15)	0.015	0.050	0.9	13
		Myclobutanil	32.99	179	150 (49)	288 (12)	0.001	0.002	1.1	12
		Ethion	33.99	231	125 (41)	153 (36)	0.001	0.004	1.2	14
		Propargite	35.50	135	173 (13)	250 (11)	0.015	0.050	1.0	15
		Tebuconazole	35.96	250	125 (100)	83 (44)	0.001	0.004	0.9	11
		Bifethrin	36.90	181	165 (79)	166 (33)	0.001	0.002	1.3	15
		Phosmet	37.38	160	104 (8)	133 (5)	0.005	0.015	0.8	14
		Phosalone	39.04	367	121 (34)	182 (29)	0.003	0.010	1.0	12
		Amitraz	49.45	121	132 (52)	147 (45)	0.006	0.020	1.1	12
		Indoxacarb	53.23	150	201 (69)	527 (32)	0.002	0.005	1.1	11
		Deltamethrin	54.06	181	253 (81)	172 (23)	0.008	0.025	0.7	14

Table 2 .

 2 Mean extraction method recoveries of pesticides from fresh nectarine,

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

Table 3

 3 Detected pesticide in peach samples in the four sampling stations, their average concentration in every sampling and the EU MRLs.

	12
								Average Concentration mg/Kg							EU MRLs
	PESTICIDES		SS 1 -AGIA VARVARA		SS -2 MELIKH			SS 3 -ALEXANDRIA			SS 4 -PLATI		(mg/Kg)
		June	July	August	September	June	July	August	September	June	July	August	September	June	July	August	September
	Diazinon	n.d.	n.d.	0.02	n.d.	n.d.	0.03	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	0.01	n.d.	0.02
	Chlorothalonil	n.d.	n.d.	0.025	n.d.	n.d.	0.04	n.d.	n.d.	n.d.	n.d.	0.025	n.d.	n.d.	n.d.	n.d.	n.d.	1.00
	Malathion	n.d.	0.05	n.d.	n.d.	n.d.	n.d.	0.04	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	0.06	n.d.	0.50
	Chlorpyriphos	0.04	0.033	0.04	0.025	n.d.	0.04	0.04	0.03	0.05	0.05	0.1	0.03	0.03	0.03	0.05	0.03	0.20
	Captan	0.1	0.1	0.07	0.07	0.1	0.1	0.06	0.05	0.08	0.07	0.1	0.04	n.d.	0.07	0.14	0.07	2.00
	Propargite	n.d.	n.d.	0.04	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	4.00
	Tebuconazole	n.d.	0.025	0.03	n.d.	n.d.	0.03	0.035	n.d.	n.d.	n.d.	0.04	n.d.	n.d.	0.03	n.d.	n.d.	1.00
	Bifethrin	n.d.	0.03	0.03	n.d.	n.d.	0.03	0.03	n.d.	n.d.	n.d.	0.02	n.d.	n.d.	n.d.	0.04	n.d.	0.20
	Phosmet	0.04	0.06	n.d.	n.d.	n.d.	n.d.	0.04	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	0.10
	Indoxacarb	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	0.06	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	n.d.	-
	13
	14	-:no defined EU MRLs, n.d.: not detected
	15
	16

Table 4 .

 4 Statistical analysis of the quantitated residual levels of the detected crop 17 protection products in peach samples from ICM system, number of detected samples, 18 average concentration, Range of concentration and European Maximum Residues

	Page 27 of 28		Food Additives and Contaminants
	19
	20	Limits
		Pesticide	Number of samples	Average concentration	Range of	EU	MRLs
			(Ν)	(mg/Kg)	concentration (mg/Kg)	(mg/Kg)
		Chlorpyriphos	46	0.036	0.025-0.1		0.20
		Tebuconazole	10	0.032	0.025-0.04		1.00
		Chlorothalonil	5	0.03	0.025-0.04		1.00
		Phosmet	7	0.05	0.04-0.06		0.10
		Captan	23	0.09	0.04-0.14		2.00
		Malathion	4	0.05	0.04-0.06		0.50
		Diazinon	5	0.02	0.01-0.03		0.02
		Bifethrin	7	0.03	0.02-0.04		0.20
		Propargite	2	0.04	0.04		4.00
		Indoxacarb	1	0.06	0.06		0.3
	21

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

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

Imathia commodity[START_REF] Tsakiris | Monitoring of pesticide residues in fresh peaches produced 477 under conventional and integrated crop management cultivation[END_REF]).

chlorothalonil and chlorpyriphos in a cranberry bog. J. Agric. Food Chem, 51:

Although the study on the monitoring of the target analytes in IPM production 363 was conducted on single samples collected in the harvest period, the study gives 364 insight into the reductions that may take place under the IPM process. The


S G Edwards
email: sedwards@harper-adams.ac.uk

Fusarium mycotoxin content of UK organic and conventional oats

Keywords: Mycotoxins -fusarium, Mycotoxins -trichothecenes, Mycotoxinszearalenone Food Types: Cereals, Organic trichothecenes, deoxynivalenol, nivalenol, HT-2 toxin, T-2 toxin, zearalenone, moniliformin, organic, conventional

Each year (2002)(2003)(2004)(2005), approximately 100 samples of oats from fields of known agronomy were analysed for 10 trichothecenes by GC/MS including deoxynivalenol (DON), nivalenol, 3-acetylDON, 15-acetylDON, fusarenone X, T-2 toxin (T2), HT-2 toxin (HT2), diacetoxyscirpenol, neosolaniol and T-2 triol. Samples were also analysed for moniliformin and zearalenone by HPLC. Of the ten trichothecenes analysed from 458 harvest samples of oat only three, 15-acetylDON, fusarenone X and diacetoxyscirpenol were not detected. Moniliformin and zearalenone were absent or rarely detected, respectively. HT2 and T2 were the most frequently detected fusarium mycotoxins, present above the limit of quantification (10 µg kg -1 ) in 92 and 84% of samples respectively, and were usually present at the highest concentrations.

The combined mean and median for HT2 and T2 (HT2 + T2) was 570 and 213 µg kg - 1 respectively. There were good correlations between concentrations of HT2 and all

other type A trichothecenes detected (T2, T2 triol and neosolaniol). Year and region had a significant effect on HT2 + T2 concentration. There was also a highly significant difference between HT2 + T2 content in organic and conventional samples with the predicted mean for organic samples five times lower than that of conventional samples. This is the largest difference reported for any mycotoxin content of organic and conventional cereals. No samples exceeded the legal limits for DON and zearalenone for oats intended for human consumption. Legislative limits for HT2 and T2 are currently under consideration by the European Commission. The levels detected in oats could have a serious consequence for the UK oat processing industry dependent on the limits set for unprocessed oats intended for human consumption.

Introduction

Fusarium head blight (FHB) of cereals may be caused by several fungal pathogens. Of these fungi, many produce a range of mycotoxins. The vast majority of research conducted on FHB is concerned with wheat as this is the most economically important small grain cereal world-wide and is the most susceptible to FHB and mycotoxin contamination in many countries. Few studies have compared the FHB severity or mycotoxin contamination of wheat, barley and oats either from replicated field experiments or observational studies.

In eastern Canada, observational data showed the highest DON content was found on wheat, then barley and lowest amounts on oats from 1991 to 1998 [START_REF] Campbell | Comparison of mycotoxin profiles among cereal samples from eastern Canada[END_REF]. The percentage of samples exceeding 1000 µg kg -1 DON was 31, 22 and 1.4% for wheat, barley and oats respectively. This data were matched in a study of ear blight susceptibility of cereal species in inoculated glasshouse experiments [START_REF] Langevin | Effect of trichothecenes produced by Fusarium graminearum during Fusarium head blight development in six cereal species[END_REF]). In the epidemic years of 1993 and 1994 in Minnesota commercial cereal samples were analysed for DON. Average DON concentrations in wheat, barley and oat samples were 8.3, 10.4, and 1.4 mg kg -1 respectively [START_REF] Jones | Quality parameters in small grains from Minnesota affected by Fusarium head blight[END_REF].

In Norway, a large scale study over 6 years identified that highest DON concentrations occurred in oat samples, then wheat, and barley had the lowest DON average concentrations [START_REF] Langseth | Differences between barley, oats and wheat in the occurrence of deoxynivalenol and other trichothecenes in Norwegian grain[END_REF]. The observed variation in contamination levels between cereals was not observed in experimental field trials indicating that the observed differences were not solely due to inherent differences in resistance but also due to differences in agronomy. There are less data as to the relative concentration of other fusarium mycotoxins in wheat, barley and oats. The type A trichothecenes, HT2 and T2 are potent inhibitors of protein synthesis and were implicated in alimentary toxic aleukia (ATA), which was responsible for many deaths in Russia in the 1940s due to the consumption of overwintered grain (Desjardins (Anon. 2006a). A combined limit for the trichothecenes HT2 and T2 will be introduced in the near future. The European Commission also set guideline limits in 2006 for fusarium mycotoxins in animal feed (Anon. 2006b). The presence of relationships between mycotoxin concentrations are important as they allow assumptions for one mycotoxin based on the concentration of another. For example, legislative limits have not been set for NIV as it is considered by the EC to be a co-contaminant of DON and as such can be controlled by controlling DON (Anon. 2006a).

There have been limited studies comparing mycotoxin concentrations in organic and conventional oat samples. A study of organic and conventional oats across six locations in Finland identified no difference in the DON concentration between organic and conventional oats [START_REF] Hietaniemi | Contents of trichothecenes in oats during official variety, organic cultivation and nitrogen fertilization trials in Finland[END_REF]). In the same study, HT2 and T2 were rarely detected above the limit of quantification (LoQ; 50 µg kg -1 ).

A more recent study [START_REF] Gottschalk | Occurrence of type A trichothecenes in conventionally and organically produced oats and oat products[END_REF], with a more sensitive methodology (LoQ < 1 µg kg -1 ) detected a high incidence of HT2 and T2 in 70 German oat and oat products and there was a significantly lower level in organic (n=35) compared to conventional (n=35) samples. However, the combined means (HT2+T2) for organic and conventional samples were both low (8 and 27 µg kg -1 respectively). The aims of the present study were: i) to identify the distribution of fusarium mycotoxins in UK oats, ii) to identify relationships between the concentrations of fusarium mycotoxins detected, iii) to identify how fusarium mycotoxin distributions vary across seasons and regions and iv) to identify if there were differences in the fusarium mycotoxin concentrations of organic and conventional oats in the UK.

Material and methods

Sample collection

Each year, from 2002-2005, about one hundred oat grain samples and related agronomic data were collected by agronomists and growers. Samples were collected at harvest from fields of known agronomy as detailed previously (Edwards, in press) Samples were collected from six geographic regions of the UK; lower numbers were collected from the East of England and Northern Ireland, this was due to the smaller areas of oats in these regions (Table I). Of a total of 458 samples collected, approximately 25% of samples were collected from organic growers (Table II).

On receipt of samples they were processed as described previously (Edwards in press). One laboratory sample was sent to RHM Technology for UKAS accredited mycotoxin analysis. A second sample was held as an archive at -20°C.

(INSERT Table 1 and 2 here)

Mycotoxin analysis

The GC-MS analysis of trichothecenes was performed by RHM Technology (High Wycombe) according to the published method [START_REF] Patel | Survey of ethnic foods for mycotoxins[END_REF]. The trichothecenes analysed for were deoxynivalenol (DON), nivalenol (NIV), 3-acetylDON, 15-acetylDON, fusarenone X, T-2 toxin (T2), HT-2 toxin (HT2), diacetoxyscirpenol (DAS), neosolaniol and T-2 triol. The limit of quantification (LoQ) was determined as six times the baseline noise and calculated to be 10 µg kg -1 .

Zearalenone was analysed by HPLC as described previously [START_REF] Scudamore | Occurrence and fate of Fusarium mycotoxins during commercial processing of oats in the UK[END_REF]. Results were adjusted according to recovery. The limit of quantification (LoQ) was determined as six times the baseline noise and calculated to be 3 µg kg -1 .

Moniliformin was also analysed by HPLC according to the method of [START_REF] Sharman | A Survey of the Occurrence of the Mycotoxin Moniliformin in Cereal Samples from Sources Worldwide[END_REF]. Results were adjusted according to recovery and the limit of quantification (LoQ) was calculated to be 10 µg kg -1 .

All methods used were UKAS accredited with acceptable recovery ranges of 70-110%. For this study the calculation of the measurement uncertainty was carried out using in-house data, performance in international collaborative trials and the Food Analysis Performance Assessment Scheme (www.fapas.co.uk/fapas.cfm) thus incorporating repeatability and reproducibility data. Only in house data was used for moniliformin as there have been no FAPAS or external collaborative trials for this mycotoxin. The expanded measurement of uncertainty was calculated using a standard coverage factor of two, equivalent to a confidence of approximately 95%

that the actual level of the mycotoxin being measured lies within the quoted range.

The expanded measurement of uncertainty was calculated to be ±25, 18 and 21% for trichothecenes, zearalenone and moniliformin respectively.

Statistical analysis

Summary statistics for each mycotoxin were calculated using Excel (Microsoft Office 2003). Statistics calculated included the percentage greater than 10 µg kg -1 (LoQ for trichothecenes), the mean, median, 90th percentile, 95th percentile and the maximum concentration for each mycotoxin detected. For the calculation of the mean, samples below the LoQ were assigned a value of (LoQ)/6, ie 1.667 for trichothecenes. This allows data to be directly compared to recently compiled fusarium mycotoxin occurrence data from EU member states [START_REF] Anon | SCOOP TASK 3.2.10. Collection of occurrence data of fusarium toxins in food and assessment of dietary intake by the population of EU member states[END_REF] For regression analysis samples below the LoQ were removed from the dataset and concentrations log 10 transformed to normalise the variance. For ANOVA of HT2+T2 samples below the LoQ were assigned a value of (LoQ)/2, ie 5 µg kg -1 , log 10 transformed to stabilise the variance and analysed using Genstat (version 10, Lawes Agricultural Trust).

Results and discussion

Mycotoxin concentration

In the first two years moniliformin was not detected in any samples (n=196) and analysis was discontinued. In the same period, zearalenone was rarely detected and when detected was only found at low concentrations, consequently analysis for zearalenone was reduced to 50 samples per year. Over four years, 296 samples were analysed for zearalenone. Five percent of samples were above the LoQ of 3 µg kg -1 and the maximum detected was 29 µg kg -1 . The legal limit for zearalenone in unprocessed oats intended for human consumption is 100 µg kg -1 (Anon. 2006a).

Of the ten trichothecenes analysed, seven were detected, of these DON, NIV, HT2, T2, neosolaniol and T2-triol were detected above 100 µg kg -1 . Table III shows the summary statistics for each trichothecene detected over the four year period.

Combined values are provided for HT2 and T2 (HT2+T2) as these closely related mycotoxins have equivalent toxicity and it is likely European legal limits will be based on a combined concentration.

DON was detected in 32% of samples and the maximum was 282 µg kg -1 ; this is well below the legal limit for DON in unprocessed oats intended for human consumption (1750 µg kg -1 ) (Anon. 2006a). HT-2 and T-2 were detected in 92 and 84% of samples respectively; the concentrations were frequently high. The combined mean, median and maximum concentrations were 570, 213 and 9990 µg kg -1 respectively. The distributions were lognormal with a left censor truncated by the LoQ. Comparison of the mean and median values for all other mycotoxins detected indicated they followed a similar lognormal distribution, however the degree of truncation of the distribution at the LoQ varied markedly. NIV was the next most common fusarium mycotoxin detected with a maximum concentration 847 µg kg -1 .

T-2 triol and neosolaniol were detected in 41% of samples and always as a low concentration, co-contaminant in the presence of a high concentration of the primary contaminants, HT2 and T2. Fusarenone X, diacetoxyscirpenol and 15-acetylDON were not detected in any sample (LoQ = 10 µg kg -1 ).

(Insert

Regression analysis

The relationships between HT2 and all other detected type A trichothecenes were analysed by regression analysis of logarithmic transformed values (Figures 123). The regressions were all highly significant (p < 0.001). Such a relationship could be expected as the type A trichothecenes are produced in the same metabolic pathway by the same species [START_REF] Thrane | Diversity in metabolite production by Fusarium langsethiae, Fusarium poae, and Fusarium sporotrichioides[END_REF]). HT2 was always detected when other type A trichothecenes were present within a sample.

There were no other positive relationships between the concentrations of other commonly detected fusarium mycotoxins detected in UK oats. In fact both NIV and DON showed signs of mutual exclusion with HT2 and to one another, ie when one mycotoxin was present at high concentration then the other was low (Figures 456).

This is probably because HT2, DON and NIV in oats are produced by different Fusarium species which appear to have different environmental requirements to each other. As a consequence of this relationship, DON concentration cannot be used to predict HT2 or NIV concentration and vice versa.

(Insert Figure 1-6 here)

Year, region and practice

The impact of practice on the combined HT2+T2 concentration was analysed using ANOVA. Year and region were entered into the model first to account for temporal and spatial variation. There was a highly significant interaction (p<0.001) between year and region with high concentrations detected in all UK regions (Figure 7). There was also a highly significant difference in the HT2+T2 concentration between organic and conventional samples (p<0.001). Organic samples were approximately five times lower, with predicted means of 50 and 264 µg kg -1 HT2+T2 for organic and conventional oats respectively. The summary statistics were determined for conventional and organic samples, and show major differences in the two datasets (Table IV). As the vast majority of oats grown in the UK are produced within conventional agriculture, then the summary statistics for this subset of samples are more representative of oat crops in the UK. A previous limit for discussion set by the EC for oats intended for human consumption was 500 µg kg -1 HT2+T2. The percentage of organic and conventional samples exceeding this discussion limit, on an annual basis, fluctuated between zero and 22 and between 18 and 50% for organic and conventional samples respectively between 2002-2005 (Table V).

(Insert Table IV and V here)

General discussion

This research has clearly identified the extent to which UK organic and conventional oats contains fusarium mycotoxins at harvest. Amounts of fusarium mycotoxins in UK oat samples from 2002-2005 were generally low. However, there were high incidences and high mean concentrations of HT2 and T2. Levels of these mycotoxins are higher than those previously reported for any cereal worldwide.

Regression analysis shows that there are strong correlations between the HT2 and the other type A trichothecenes (T2, T2 triol and NEO), which would indicate that they are produced by the same Fusarium isolates as part of the same synthetic pathway and therefore are co-contaminants. This is of benefit as it would allow an estimate of the content of other type A trichothecenes if the concentration of one of them is known. This is of use as current ELISA analysis kits can detect T2 but crossreact at a known rate with HT2. By knowing the proportion of HT2 to T2 and the cross-reaction ratio then the total content of HT2+T2 can be estimated using ELISA analysis of T2. The regression also indicates that methods to reduce one type A trichothecene should result in overall reduction of all type A trichothecenes.

Regression analysis of HT2+T2 against DON and NIV and the regression of DON against NIV suggests some degree of mutual exclusion indicating that the species responsible either compete against one another or prefer different environmental conditions. These results agree with the relationships between trichothecenes determined on wheat (Edwards In press) and reinforces the conclusion that DON and NIV are not co-contaminants and should not be treated as such within European legislation.

Modelling of HT2+T2 concentration of oat samples against year, region and practice identified a highly significant interaction between year and region. This is probably due to fluctuation in weather between years and regions. There was no trend from North to South, as seen for DON in wheat (Edwards In press), which would indicate that the temperature difference across the UK is not restrictive to HT2 and T2 production on oats. This is different from DON in wheat where there was a lower concentration in the North of Britain. Oat samples with more than 500 ppb HT2+T2

were detected in all regions of the UK at similar frequencies. The highest concentration of HT2+T2 occurred in 2005, which was a relatively dry summer. High levels of HT2+T2 were not seen in 2004, when DON and zearalenone were highest on wheat after a wet harvest (Edwards In press). This would indicate that the HT2+T2producing Fusarium species probably have different environmental requirements than F. culmorum and F. graminearum, which produce DON and prefer wet conditions.

There was a five-fold difference in the predicted mean HT2+T2 content of conventional and organic oat samples with organic samples having a significantly lower HT2 and T2 content compared to conventional oats. Previous studies of organic and conventional oat and oat products have identified lower concentrations of HT2 and T2 in organic samples, but the difference was not as great as reported here [START_REF] Gottschalk | Occurrence of type A trichothecenes in conventionally and organically produced oats and oat products[END_REF]. Organic oats may have a lower HT2 and T2 content due to a number of agronomic factors. These could include previous crop, cultivation and varietal choice. Organic growers tend to have longer rotations which are more diverse and less cereal intensive than conventional growers. This could result in a lower level of the HT2+T2-producing Fusarium inoculum within organic production,. A recent UK wheat project identified a significantly lower (ca. two-fold) incidence of HT2+T2 in organic compared to conventional samples although the incidence and concentration of these mycotoxins were much lower in wheat (Edwards In press).

The same study found no significant difference between DON in organic and conventional wheat (Edwards In press).

UK oats in general had a high content of HT2 and T2. This is the first reported study on mycotoxin content of oats at harvest in the UK. Until legislative limits for HT2+T2 are set, the extent to which these limits will impact on the UK oat industry cannot be determined.

The presence of HT2 and T2, although at a lower concentration than identified in this paper, were first reported in oats in Norway [START_REF] Langseth | Differences between barley, oats and wheat in the occurrence of deoxynivalenol and other trichothecenes in Norwegian grain[END_REF] and T2 concentration in oats appears to be increasing in Sweden in recent years. UK results differ from those in Nordic countries, where high DON can also occur [START_REF] Langseth | Differences between barley, oats and wheat in the occurrence of deoxynivalenol and other trichothecenes in Norwegian grain[END_REF][START_REF] Langseth | The occurrence of deoxynivalenol in Norwegian cereals -Differences between years and districts, 1988-1996[END_REF][START_REF] Langseth | The occurrence of HT-2 toxin and other trichothecenes in Norwegian cereals[END_REF][START_REF] Scudamore | Occurrence and fate of Fusarium mycotoxins during commercial processing of oats in the UK[END_REF]). In Canada, DON is routinely detected in oat and oat products, but analysis of HT2 and T2 are not reported [START_REF] Tekauz | Fusarium head blight of oatcurrent status in western Canada[END_REF] or when analysed are rarely detected [START_REF] Roscoe | Mycotoxins in breakfast cereals from the Canadian retail market: A 3-year survey[END_REF]. Of concern is that little is known about the Fusarium species that produce HT2 and T2 or the factors involved in the presence of HT2 and T2 on cereals and cereal products. Further research on this topic is documented within current European legislation as necessary and of a high priority (Anon. 2006a).

Legislative limits for HT2 and T2 are currently under consideration by the European Commission. A previous limit of 500 µg kg -1 HT2+T2 for unprocessed oats was set for discussion. A study of industrial processing of oats has identified that the majority (>90%) of the HT2 and T2 is on the husk which is removed during processing [START_REF] Scudamore | Occurrence and fate of Fusarium mycotoxins during commercial processing of oats in the UK[END_REF], resulting in much lower levels detected in finished products. During the period of this study, the levels of HT2 and T2 detected during a survey of fusarium mycotoxins in retail oat products were low, and deemed not of concern [START_REF] Anon | SCOOP TASK 3.2.10. Collection of occurrence data of fusarium toxins in food and assessment of dietary intake by the population of EU member states[END_REF]). However, the EC sets legislative limits on unprocessed cereals as well as finished products. Therefore, the concentrations of HT2 and T2 in oats determined in this study could have serious consequences for the UK oat processing industry. How serious, is dependent on the limits set for HT2 and T2 in unprocessed oats intended for human consumption.

F

Figure 1 .

 1 Figure 1. Regression of T2 against HT2 concentration (log log plot) for UK oats from 2002 to 2005 (n = 458). Regressions fitted for all samples above LoQ.

Figure 2 .

 2 Figure 2. Regressions of neosolaniol against HT2 concentration (log log plot) for UK oats from 2002 to 2005 (n = 458). Regressions fitted for all samples above LoQ.

Figure 3 .

 3 Figure 3. Regressions of T2 triol against HT2 concentration (log log plot) for UK oats from 2002 to 2005 (n = 458). Regressions fitted for all samples above LoQ.

Figure 4 .

 4 Figure 4. Relationship between HT2 and DON concentration for UK oats 2002-2005 (n=458).

Figure 5 .

 5 Figure 5. Relationship between HT2 and NIV concentration for UK oats 2002-2005 (n=458).

Figure 6 .

 6 Figure 6. Relationship between NIV and DON concentration for UK oats 2002-2005 (n=458).

Figure 7 .

 7 Figure 7. Predicted mean HT2+T2 concentration for UK oats from each region in each year. Bars represent 95% confidence limits for predictions.

  The distribution of these mycotoxins is largely limited to Europe, although this may, in part, be due to the lack of analysis in other regions of the world. Until recently, the concentrations of HT2 and T2 detected in cereal samples were relatively low with higher levels detected on oats, then barley and lowest in wheat samples in

	2006). Norway (Langseth and Rundberget 1999). Recently, higher concentrations of HT2
	and T2 have been detected in oats in Nordic countries and the UK (Pettersson 2007,
	Scudamore et al. 2007). Moniliformin has been detected in cereal samples from
	Nordic countries. In Norway, highest levels were observed on wheat, with similar, F lower amounts on barley and oats (Uhlig et al. 2004). There are limited data on occurrence of fusarium mycotoxins in UK cereals prior to 2001. A previous survey o r conducted in 1999 found highest amounts of DON on wheat, with lower levels on
	barley and oats (MacDonald et al. 2004). Other trichothecenes were not analysed P within this study. e The European Commission (EC) has set legislative limits for the fusarium e r mycotoxins including the trichothecene, DON and ZON in cereal grains and cereal-
	R based products intended for human consumption
	e
	v i e
	w
	O n l
	y

Table 3 here)

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

Table I .

 I Uhlig S, Torp M, Jarp J, Parich A, Gutleb AC, Krska R. 2004. Moniliformin in Norwegian grain. Food Additives and Contaminants 21:598-606. Sample distribution by year and region.

	Reading. This research was funded by the UK Food Standards Agency (CO4033 and
	CO4034) and Home-Grown Cereal Authority (RD-2002-2706).
				Region
	Year							Total
		South	East	Midlands	North	Scotland N.Ireland
	2002	14	12	27	13	11	15	92
	2003	22	5	16	22	27	12	104
	2004	22	19	27	33	18	9	128
	2005	27	17	33	27	21	9	134
	Total	85	53	103	95	77	45	458
		o r P e e r R e v i e w O n l F o r P e e r R e v i e w O n o r P e e r R e v i e w F o r P e e r R e v i e w l F O n l O n l
							y y y

Table II .

 II Sample distribution by year and practice. Based on a value of 1.667 for all samples below the limit of quantification (10 µg kg - 1 ).

	F o r
	Year 2002	Organic P 30 e	Practice Conventional 62	Total 92
	2003 2004 2005		45 14 26 e r	59 114 108	104 128 134
	Total		115	R	343	458
						e
	Table III. Concentrations of all trichothecene mycotoxins detected in UK oats in 2002-2005 (458 samples). v i e
						Mycotoxin concentration (µg kg -1 ) w
	DON 3AcDON NIV Neosolaniol T-2 triol	% > 10 µg kg -1 32 0.2 72 41 41	Mean a 11 <10 49 14 17	Median 0 <10 24 <10 <10	90th% 24 <10 120 38 O 95th% 50 <10 176 53 n l 46 68 y	Max 282 26 847 189 263
	T-2		84	140	58		389	502	2406
	HT-2		92	430	151		1110	1727	7584
	HT2+T2		92	570	213		1492	2160	9990

a

Table IV .

 IV Concentration of HT2+T2 detected in conventional (n = 343) and organic (n = 115) UK oats in 2002-2005.

				HT2+T2 concentration (ppb)
		%>10ppb Mean	Median	90th%	95th%	Max
	Conventional	97	687	292	1704	2450	9990
	Organic	78	238	49	515	703	8684

Table V .

 V Percentage of UK oat samples (n=458) exceeding 500 µg kg -1 HT2+T2.

	Year	Conventional	Organic	Overall
	2002	18	13	16
	2003	41	22	33
	2004	31	0	24
	2005	50	8	42
	Overall	36	11	30

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

Acknowledgements

I would like to acknowledge all growers who supplied samples and the agronomists from the Association of Independent Crop Consultants, Agrovista and the Department of Agriculture and Rural Development in Northern Ireland who co-ordinated collection of samples. Technical support at Harper Adams was provided by Luda Ibrahim, Katerina Pirgozlieva and Rumiana Ray of the Molecular Diagnostics Laboratory and the field trial officers of the Crop and Environment Research Centre. Mycotoxin analysis was conducted by Sue Patel at RHM Technology. Statistical advice was provided by Sandro Leidi at Statistical Services Centre, University of


S G Edwards
email: sedwards@harper-adams.ac.uk

Fusarium mycotoxin content of UK organic and conventional barley

Keywords: Mycotoxins -fusarium, Mycotoxins -trichothecenes, Mycotoxinszearalenone Food Types: Cereals trichothecenes, deoxynivalenol, nivalenol, HT-2 toxin, T-2 toxin, zearalenone, moniliformin, organic, conventional

Each year (2002)(2003)(2004)(2005), approximately 100 samples of barley from fields of known agronomy were analysed for 10 trichothecenes by GC/MS including deoxynivalenol (DON), nivalenol, 3-acetylDON, 15-acetylDON, fusarenone X, T-2 toxin (T2), HT-2 toxin (HT2), diacetoxyscirpenol, neosolaniol and T-2 triol. Samples were also analysed for moniliformin and zearalenone by HPLC. Of the 10 trichothecenes analysed from 446 harvest samples of barley only two, diacetoxyscirpenol and neosolaniol were not detected. The concentration of type A trichothecenes were similar to those that occurred in wheat over the same period whilst those of type B trichothecenes were markedly lower. Deoxynivalenol was the most frequently detected Fusarium mycotoxin, present above the limit of quantification (10 µg kg -1 ) in 57% of samples, and was usually present at the highest concentration. A single sample (0.2%) exceeded the legal limit for DON in unprocessed barley over the fouryear period. Moniliformin and zearalenone were both rarely detected (2% of samples greater than 10 µg kg -1 for both toxins) with maximum concentrations of 45 and 44 µg kg -1 respectively. Year and region had a significant effect on DON and HT2+T2 but there was no significant difference in the concentration of these mycotoxins between organic and conventional samples. Overall, the risk of UK barley exceeding the newly introduced legal limits for Fusarium mycotoxins in cereals intended for human consumption is very low, but the percentage of samples above these limits will fluctuate between years.

Introduction

All cereal crops are prone to Fusarium head blight and resulting contamination of harvested grains by Fusarium mycotoxins. Of the cereal species durum wheat, followed by soft wheat are usually the most susceptible. Barley, rye and oats are considered less susceptible [START_REF] Langevin | Effect of trichothecenes produced by Fusarium graminearum during Fusarium head blight development in six cereal species[END_REF]) although there is considerable variation between geographic regions. In eastern Canada, the DON concentration of barley was lower than in wheat [START_REF] Campbell | Comparison of mycotoxin profiles among cereal samples from eastern Canada[END_REF], whereas in Minnesota during the epidemics of 1993 and 1994 the average DON content of Barley was higher than that for wheat [START_REF] Jones | Quality parameters in small grains from Minnesota affected by Fusarium head blight[END_REF]. A study in Norway found higher DON concentrations on oats, then barley and least on wheat samples [START_REF] Langseth | Differences between barley, oats and wheat in the occurrence of deoxynivalenol and other trichothecenes in Norwegian grain[END_REF]. There are limited data on occurrence of Fusarium mycotoxins in UK cereals prior to 2001. A previous survey conducted in 1999 found highest amounts of DON on wheat, with lower levels on barley and oats [START_REF] Macdonald | Survey of ochratoxin A and deoxynivalenol in stored grains from the 1999 harvest in the UK[END_REF].

There are less data as to the relative concentration of other Fusarium mycotoxins in wheat, barley and oats. For HT2 and T2, highest levels were detected on oats, then barley and lowest in wheat samples in Norway [START_REF] Langseth | The occurrence of HT-2 toxin and other trichothecenes in Norwegian cereals[END_REF]. Moniliformin has been detected in cereal samples from Nordic countries. In Norway, highest levels were observed on wheat, with similar, lower amounts on barley and oats [START_REF] Uhlig | Moniliformin in Norwegian grain[END_REF].

The European Commission (EC) has set legislative limits for the Fusarium mycotoxins including the trichothecene, DON and ZON in cereal grains and cerealbased products intended for human consumption (Anon. 2006a). A combined limit for the trichothecenes HT2 and T2 will be introduced in the near future. The European Commission also set guideline limits in 2006 for Fusarium mycotoxins in animal feed (Anon. 2006b). The presence of relationships between mycotoxin concentrations are important as they allow assumptions for one mycotoxin based on the concentration of another. For example, legislative limits have not been set for NIV as it is considered by the EC to be a co-contaminant of DON and as such can be controlled by controlling DON (Anon. 2006a). Relationships between mycotoxins also provide evidence of the relationships that may exist between the Fusarium species that produce these mycotoxins.

Several studies have compared the mycotoxin content of wheat and wheat products in organic and conventional samples. These studies have either identified no differences [START_REF] Champeil | Influence of cropping system on Fusarium head blight and mycotoxin levels in winter wheat[END_REF][START_REF] Jestoi | Levels of mycotoxins and sample cytotoxicity of selected organic and conventional grain-based products purchased from Finnish and Italian markets[END_REF] or found slightly less DON in organic samples [START_REF] Schollenberger | Fusarium toxins in wheat flour collected in an area in southwest Germany[END_REF][START_REF] Schollenberger | Trichothecene toxins in different groups of conventional and organic bread of the German market[END_REF]. No studies have been conducted on barley, although one study in Belgium compared levels of DON in organic and conventional beers and found no significant differences [START_REF] Anselme | Comparison of ochratoxin A and deoxynivalenol in organically and conventionally produced beers sold on the Belgian market[END_REF].

The aims of the present study were: i) to identify the distribution of Fusarium mycotoxins in UK barley, ii) to identify relationships between the concentrations of Fusarium mycotoxins detected, iii) to identify how Fusarium mycotoxin distributions vary across seasons and regions and iv) to identify if there were differences in the Fusarium mycotoxin concentrations of organic and conventional barley in the UK. Each year, from 2002-2005, about one hundred barley grain samples and related agronomic data were collected by agronomists and growers. Samples were collected at harvest from fields of known agronomy as detailed previously (Edwards In press a). Near equivalent numbers of samples were collected from six geographic regions of the UK (Table I). Of a total of 446 samples collected, approximately 25% of samples were collected from organic growers (Table II).

Material and methods

Sample collection

On receipt of samples they were processed as described previously (Edwards In press a). 1 and2 here)

(INSERT Table

Mycotoxin analysis

All mycotoxin analysis was conducted by RHM Technology (High Wycombe). Ten trichothcenes (deoxynivalenol (DON), nivalenol (NIV), 3-acetylDON, 15-acetylDON, fusarenone X, T-2 toxin (T2), HT-2 toxin (HT2), diacetoxyscirpenol (DAS), neosolaniol and T-2 triol) were quantified by GC/MS and zearalenone and moniliformin were quantified by HPLC using previously published methods [START_REF] Sharman | A Survey of the Occurrence of the Mycotoxin Moniliformin in Cereal Samples from Sources Worldwide[END_REF][START_REF] Patel | Survey of ethnic foods for mycotoxins[END_REF][START_REF] Scudamore | Occurrence and fate of Fusarium mycotoxins during commercial processing of oats in the UK[END_REF]). The limit of quantification (LoQ) was determined as six times the baseline noise and calculated to be 10 µg kg -1 for trichothecenes and moniliformin and 3 µg kg -1 for zearalenone.

All methods used were UKAS accredited with acceptable recovery ranges of 70-110%. For this study the calculation of the measurement uncertainty was carried out using in-house data, performance in international collaborative trials and the Food Analysis Performance Assessment Scheme (www.fapas.co.uk/fapas.cfm) thus incorporating repeatability and reproducibility data. Only in house data was used for moniliformin as there have been no FAPAS or external collaborative trials for this mycotoxin. The expanded measurement of uncertainty was calculated using a standard coverage factor of two, equivalent to a confidence of approximately 95% that the actual level of the mycotoxin being measured lies within the quoted range. The expanded measurement of uncertainty was calculated to be ±25, 18 and 21% for trichothecenes, zearalenone and moniliformin respectively.

Statistical analysis

Summary statistics for each mycotoxin were calculated using Excel (Microsoft Office 2003). Statistics calculated included the percentage greater than 10 µg kg -1 (LoQ for trichothecenes), the mean, median, 90th percentile, 95th percentile and the maximum concentration for each mycotoxin detected. For the calculation of the mean, samples below the LoQ were assigned a value of (LoQ)/6, ie 1.667 for trichothecenes. This allows data to be directly compared to recently compiled Fusarium mycotoxin occurrence data from EU member states [START_REF] Anon | SCOOP TASK 3.2.10 Collection of occurrence data of fusarium toxins in food and assessment of dietary intake by the population of EU member states[END_REF] For regression analysis samples below the LoQ were removed from the dataset and concentrations log 10 transformed to normalise the variance. For ANOVA samples below the LoQ were assigned a value of (LoQ)/2, ie 5 µg kg -1 for trichothecenes; log 10 transformed to stabilise the variance and analysed using Genstat (version 10, Lawes Agricultural Trust). For mycotoxins with a low number of detectable samples, the mycotoxin distribution was analysed by analysis of deviance of incidence data and ANOVA of positive samples. For analysis of deviance samples below the LoQ were allocated a value of zero, those above the LoQ were allocated a value of one and analysed using a Bernoulli distribution with Genstat.

Results and discussion

Mycotoxin concentration

In the first two years moniliformin was only detected above 10 µg kg -1 in 2% of samples (n=239); the maximum was 45 µg kg -1 . Consequently analysis of moniliformin was not performed in the final two years. In the same period, zearalenone was rarely detected and when detected was only found at low concentrations, consequently analysis for zearalenone was reduced to 50 samples per year. Over four years, 339 samples were analysed for zearalenone. Ten percent of samples were above the LoQ of 3 µg kg -1 , 2% of samples exceeded 10 µg kg -1 and the maximum detected was 44 µg kg -1 . The legal limit for zearalenone in unprocessed barley intended for human consumption is 100 µg kg -1 (Anon. 2006a).

Of the ten trichothecenes analysed, eight were detected, of these DON, NIV, and HT2 were detected above 100 µg kg -1 . Table III shows the summary statistics for each trichothecene detected over the four year period. Combined values are provided for HT2 and T2 (HT2+T2) as these closely related mycotoxins have equivalent toxicity and it is likely European legal limits will be based on a combined concentration.

DON was detected in 57% of samples and one sample (0.2% of total) exceeded the legal limit for DON in unprocessed barley intended for human consumption (1250 µg kg -1 ) (Anon. 2006a). This sample, harvested in 2005, had a DON concentration of 1416 µg kg -1 . This was the only sample with detectable 3-and 15-acetyl DON as co-contaminants of DON. HT-2 and T-2 were detected in 36 and 12% of samples respectively; the concentrations were not high compared with UK oats (Edwards In press b). One point one percent of samples exceeded 100 µg kg -1 and the combined maximum concentration was 138 µg kg -1 HT2+T2. Nivalenol, although relatively common (detected in 25% of samples) was not found at high concentrations (maximum 157 µg kg -1 ). Fusarenone X, an acetylated version of nivalenol, was detected at low concentrations in four samples in 2004. This trichothecene has not been reported in UK cereals previously, including the two recent studies of wheat and oats (Edwards In press a, In press b). T2 triol was detected just above the limit of quantification in a single sample as a co-contaminant of HT2 and T2, in the same year. Diacetoxyscirpenol and neosolaniol were not detected in any sample (LoQ = 10 µg kg -1 ).

(Insert Table 3 here)

Regression analysis

The relationship between HT2 and T2 was analysed by regression analysis of logarithmic transformed values (Figure 1). The regression was highly significant (p < 0.001) and accounted for 37% of the variance. There were no other positive relationships between the concentrations of other commonly detected Fusarium

Year, region and practice

The impact of practice on the DON concentration was analysed using ANOVA. Year and region were entered into the model first to account for temporal and spatial variation. There was a highly significant interaction (p=0.003) between year and region with higher concentrations been detected in the South, declining northwards (Figure 5). There was no significant difference in DON concentration between organic and conventional samples (p=0.263).

The low incidence of samples with HT2+T2 above the limit of quantification resulted in the residuals were not normally distributed, consequently the concentration of these mycotoxins could not be analysed by ANOVA. Incidence of HT2+T2 was analysed by analysis of deviance using a Bernoulli distribution. Concentration of HT2+T2 was then analysed for the subset of samples with concentrations above the limit of quantification using ANOVA. As for DON analysis, year and region were entered into the models first to account for temporal and spatial variation. For HT2+T2 incidence there were highly significant differences between years (p<0.001) and regions (p<0.001) but no significant interaction (p=0.316) (Figure 6A). There was no significant difference (p=0.362) in the HT2+T2 incidence of organic and conventional samples. ANOVA of HT2+T2 concentration in positive samples (n=159) indicated a significant interaction between year and region (p=0.004) (Figure 6B) but no significant difference between organic and conventional samples (p=0.839).

There were too few samples with detectable zearalenone to allow any statistical analysis.

General discussion

This research has clearly identified the extent to which UK organic and conventional barley contains Fusarium mycotoxins at harvest. Amounts of Fusarium mycotoxins in UK barley samples from 2002-2005 were generally low. In comparison to wheat, barley levels of all mycotoxins were much lower except for HT2 and T2, which were present at similar concentrations. Only a single barley sample (0.2% of total) exceeded the newly introduced limit of 1250 µg kg -1 DON in unprocessed cereals intended of human consumption.

Regression analysis showed a weak relationship between HT2 and T2. This is similar to the correlation reported for these related type A trichothecenes in wheat, which had a similar incidence and concentration range (Edwards In press a). Both wheat and barley had much weaker correlations between HT2 and T2 compared with oats which had a high incidence and wide concentration range of these mycotoxins (Edwards In press b). Scatter plots of HT2+T2 against DON and NIV and of DON against NIV were similar to those reported for wheat and oats. There was a consistent pattern of mutual exclusion at high concentrations. This would indicate that the species responsible for the production of DON, NIV and HT2+T2 either compete actively against one another, or prefer different environmental conditions.

Modelling of DON concentration of barley samples against year, region and practice identified a highly significant interaction between year and region. There was the same trend from North to South, as seen for DON in wheat (Edwards In press a), with a lower concentration in the North of Britain. This distribution matches the distribution of F. graminearum on wheat in the UK [START_REF] Anon | Incidence of FHB in winter wheat[END_REF].

There was no significant difference in the mycotoxin content of organic and conventional barley samples. Recent studies have identified significantly lower HT2 and T2 in UK wheat and oats (Edwards In press a, In press b). Why differences were not detected in barley, compared with wheat, which had similar incidence and concentrations may be due to weaker statistical strength of the test, as fewer barley samples (n=446) were analysed compared with wheat (n=1624); or differences in the agronomy of conventional and organic barley compared with wheat resulting in lower HT2+T2 in organic wheat but not organic barley.

The relative levels of Fusarium mycotoxins in UK wheat, barley and oats are different to those observed in other countries (Langseth andElen 1996, Campbell et al. 2002). Differences between countries in the relative level of Fusarium mycotoxins between cereals hosts maybe due to genetic, meteorological or agronomical differences. Comparison of Fusarium head blight infection of different cereal hosts under controlled conditions has identified genetic differences [START_REF] Langevin | Effect of trichothecenes produced by Fusarium graminearum during Fusarium head blight development in six cereal species[END_REF]) and comparison of replicated field trials to survey data has shown differences also occur due to climatic and/or agronomic factors [START_REF] Langseth | Differences between barley, oats and wheat in the occurrence of deoxynivalenol and other trichothecenes in Norwegian grain[END_REF]. High concentrations of HT2 and T2 were recently reported in French barley [START_REF] Barrier-Guillot | T2 and HT2 in cereals grown in France[END_REF]. Why these should occur in France and not other countries is not known and should be determined to help maintain low HT2 and T2 in barley worldwide. a Based on a value of 1.667 for all samples below the limit of quantification (10 µg kg - 1 ).

F

  UK barley. Both NIV and DON showed signs of mutual exclusion with HT2 and to one another (Figures2-4).

Figure 1 .

 1 Figure 1. Relationship between T2 and HT2 concentration for UK barley 2002-2005 (n=446). Regression fitted for all samples above LoQ.

Figure 2 .

 2 Figure 2. Relationship between nivalenol and deoxynivalenol concentration for UK barley 2002-2005 (n=445; one outlier excluded with DON and NIV concentration 1416 and 47 µg kg -1 respectively).

Figure 3 .

 3 Figure 3. Relationship between HT2+T2 and deoxynivalenol concentration for UK barley 2002-2005 (n=445; one outlier excluded with DON and HT2+T2 concentration 1416 and 56 µg kg -1 respectively).

Figure 4 .Figure 5 .

 45 Figure 4. Relationship between nivalenol and HT2+T2 concentration for UK barley 2002-2005 (n=446).

Figure 6 .

 6 Figure 6. Predicted HT2+T2 incidence (A) and mean concentration of positive samples (B) for UK barley from each region in each year. Bars represent 95% confidence limits for predictions.

Table I .

 I Sample distribution by year and region.

	Year	South	East	Region Midlands North	Scotland	N.Ireland	Total
	2002	27	14	20	17	14	19	111
	2003	21	20	17	25	21	24	128
	2004	17	17	24	23	14	15	110
	2005	12	15	23	15	19	13	97
	Total	77	66	84	80	68	71	446
		o r F o r F o r
			P P P
			e e e
			e r e r e r
				R R R
				e e e
				v i e v i e v i e
					w w w
					O n l O n l O n l
						y y y

Table II .

 II Sample distribution by year and practice.

	Year		Practice Organic Conventional	Total
	2002		36	75		111
	2003		35	93		128
	2004		23	87		110
	2005		14	83		97
	Total		108	338		446
	Table III. Concentrations of all trichothecene mycotoxins detected in UK barley in
			2002-2005 (446 samples).
				Mycotoxin concentration (µg kg -1 )
	%>10
	µg kg -1 Mean a Median	90th%	95th%	Max
	DON	57	19	11	35	50 1416
	15AcDON	0.5	<10	<10	<10	<10	35
	3AcDON	0.2	<10	<10	<10	<10	15
	NIV	25	<10	<10	24	45	157
	FUS-X	0.7	<10	<10	<10	<10	55
	T2 triol	0.2	<10	<10	<10	<10	11
	T2	12	<10	<10	11	17	39
	HT2	36	10	<10	28	45	105
	HT2+T2	36	<20	<20	37	64	138

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

Acknowledgements

I would like to acknowledge all growers who supplied samples and the agronomists from the Association of Independent Crop Consultants, Agrovista and the Department of Agriculture and Rural Development in Northern Ireland who co-ordinated collection of samples. Technical support at Harper Adams was provided by Luda Ibrahim, Katerina Pirgozlieva and Rumiana Ray of the Molecular Diagnostics Laboratory and the field trial officers of the Crop and Environment Research Centre. Mycotoxin analysis was conducted by Sue Patel at RHM Technology. Statistical advice was provided by Sandro Leidi at Statistical Services Centre, University of Reading. This research was funded by the UK Food Standards Agency (CO4033 and CO4034) and Home-Grown Cereal Authority (RD-2002-2706).