Maria Victoria Selma
email: mvselma@cebas.csic.es

Pedro V Martínez-Culebras

Patricia Elizaquivel

Rosa Aznar

Maria ; Cebas-Csic

P Elizaquível

Simultaneous detection of the main black aspergilli responsible for OTA

Keywords: Aspergillus carbonarius, Aspergillus niger aggregate, Aspergillus tubingensis, 42 grapes, Mycotoxin, Ochratoxin A, Polyketide synthase, Real-time PCR, Wine

Introduction 47

Ochratoxin A (OTA) is a mycotoxin with nephrotoxic, carcinogenic, immunotoxic, 48 genotoxic and teratogenic effects, which has been associated with Balkan Endemic 49 Nephropathy [START_REF] Krogh | Causal associations of mycotoxic nephropathy[END_REF][START_REF] Kuiper-Goodman | Risk assessment of the mycotoxin ochratoxin A[END_REF][START_REF] Abouzied | Ochratoxin A 399 concentrations in food and feed from a region with Balkan endemic nephropathy[END_REF]. In the 50 European diet, wine and especially red wine, has been identified as the second major source 51 of human exposure to OTA, following cereals (Anonymous 1998). As a consequence, the 52 European Commission has considered the need of imposing regulatory limits and has 53 established 2 ng g -1 as the maximum level of OTA in wine and grape products 54 ochratoxin A) [START_REF] Varga | Ochratoxin A in grapes and grape derived products[END_REF]. 56

Aspergillus species belonging to section Nigri, commonly known as black aspergilli in 57 particular, Aspergillus carbonarius and species belonging to the Aspergillus niger 58 aggregate, have been identified as the main fungi responsible for OTA contamination in 59 grapes and wine (for an overview see [START_REF] Abarca | Aspergillus 395 carbonarius as the main source of ochratoxin A contamination in dried vine fruits from 396 the Spanish market[END_REF][START_REF] Samson | New 469 ochratoxin A or sclerotium producing species in Aspergillus section Nigri[END_REF]Battilani et al. 60 2006). A. carbonarius is considered the mayor responsible for OTA contamination in 61 grapes because the reported percentages of OTA-producing strains in this species are higher 62 than those reported for members of the A. niger aggregate. Nevertheless, the black 63 aspergilli most frequently isolated from grapes are species belonging to the A. niger 64 aggregate, mainly A. niger and Aspergillus tubingensis [START_REF] Cabañes | 422 What is the source of ochratoxin A in wine?[END_REF]Abarca et al. 65 2003;[START_REF] Battilani | Occurrence 410 of ochratoxin A-producing fungi in grapes grown in Italy[END_REF][START_REF] Bellí | Occurrence of ochratoxin 416 A and toxigenic potential of fungal isolates from Spanish grapes[END_REF]2006;[START_REF] Martínez-Culebras | An ITS-RFLP method to identify black 448 Aspergillus isolates responsible for OTA contamination in grapes and wine[END_REF]. 66 Recently, Martínez-Culebras & Ramón (2007) reported the existence of a new OTA 67 producing group of strains, frequently found in grapes, which is related to A. tubingensis 68 and might be considered within the A. niger aggregate. These data provide strong evidence 69 Multiplex real-time PCR allows the simultaneous amplification of more than one target 75 sequence in a single reaction. This saves considerable time and effort, and decreases the 76 number of reactions that need to be performed to detect fungal pathogens in vegetable 77 samples [START_REF] Brandfass | Simultaneous detection of Fusarium culmorum and 419 Fusarium graminearum in plant material by duplex PCR with melting curve analysis[END_REF]. Several real-time PCR assays have proven useful 78 in monitoring and quantification of OTA-producing fungi such as Penicillium nordicum 79 [START_REF] Geisen | Development of a real time PCR system 430 for detection of Penicillium nordicum and for monitoring ochratoxin A production in 431 foods by targeting the ochratoxin poliketide synthase gene[END_REF]) and Aspergillus ochraceus [START_REF] Schmidt | Detection and quantification of 478 Aspergillus ochraceus in green coffee by PCR[END_REF]). Regarding black 80 aspergilli, single real-time PCR assays for the detection and quantification of A. 81 carbonarius have been described [START_REF] Mulè | Development of a quantitative 451 real-time PCR assay for the detection of Aspergillus carbonarius in grapes[END_REF][START_REF] Atoui | Targeting a polyketide synthase gene for Aspergillus 405 carbonarius quantification and ochratoxin A assessment in grapes using real-time PCR[END_REF][START_REF] Selma | Real-time PCR based procedures for 481 detection and quantification of Aspergillus carbonarius in wine grapes[END_REF]. 82 However, no real-time PCR assay is currently available for the simultaneous quantitative 83 detection of A. carbonarius and species belonging to the A. niger aggregate. 84

A specific real-time PCR assay for the quantitative detection of A. carbonarius in 85 combination with a rapid and efficient fungi DNA extraction procedure has already been 86 developed [START_REF] Selma | Real-time PCR based procedures for 481 detection and quantification of Aspergillus carbonarius in wine grapes[END_REF]. This assay targets a 161 bp fragment in the β-ketosynthase 87 domain of a polyketide synthase (PKS) from A. carbonarius. DNA extraction procedure 88 includes a pulsifier equipment to remove conidia from grapes which prevents releasing of 89 PCR inhibitors. It is highly selective, sensitive and suitable for the accurate quantification 90 of all strains of A. carbonarius. In the present study, we describe a duplex real-time PCR 91 assay that combines the A. carbonarius-specific β-ketosynthase domain assay and the 92

Materials and Methods 95

Fungal strains and growth conditions 96 Black Aspergillus strains were isolated from Spanish vineyards and are held in the Institute 97 of Agrochemistry and Food Technology (IATA-CSIC). They were previously identified by 98 ITS-RFLP profiles and tested for OTA-production [START_REF] Martínez-Culebras | An ITS-RFLP method to identify black 448 Aspergillus isolates responsible for OTA contamination in grapes and wine[END_REF]. 99

Reference strains were provided by Centralbureau voor Schimmelcultures (CBS, Utrecht, 100

The Netherlands) and the Spanish Type Culture Collection (CECT, Valencia, Spain) (see 101

Table 1). The reference strains used in the present study were previously tested for OTA 102 production [START_REF] Samson | New 469 ochratoxin A or sclerotium producing species in Aspergillus section Nigri[END_REF][START_REF] Martínez-Culebras | Acyl transferase 443 domains of putative polyketide synthase (PKS) genes in Aspergillus and Penicillium 444 producers of ochratoxin A and the evaluation of PCR primers to amplify PKS 445 sequences in black Aspergillus species[END_REF]. They were all grown in 103 Malt Extract Agar (MEA) plates at 25 ± 1 ºC for 5-7 days [START_REF] Pitt | Fungi and Food Spoilage[END_REF]. 104 105 Fungal and grape DNA isolation 106 Mycelia were collected from cultures growing on MEA plates frozen in liquid nitrogen and 107 ground to a fine powder. Fungal DNA extractions were performed using 100 mg of powder 108 and the commercial EZNA Fungal DNA kit (Omega bio-teck, Doraville, USA) according 109 to the manufacturer's instructions. Accurate DNA quantification for real-time PCR assays 110 was approached using the 'Fluorescent DNA Quantitation Kit' (BioRad, California, USA) 111 and a VersaFluor® spectrofluorimeter (BioRad, California, USA) 112

For grape DNA extraction, 25 g of grapes were homogenized in 100 mL of sterile 0.1 % 113 buffered peptone water (BPW, AES Laboratoire, Combourg, France) using a pulsifier 114 equipment (Microgen bioproducts, Surrey, UK). One milliliter of pulsified grape samples 115 were centrifuged for 3 min at 13,000 g. Pellets were washed in 0.5 mL of TE (10 mmol L 1). They included 42 strains belonging to Aspergillus 151 species and 5 to other fungal species commonly isolated from grapes. PCR reactions using 152 the A. niger aggregate specific primers AtNig1 / AtNig2 and the universal primers its5/its4 153 [START_REF] White | Amplification and direct sequencing of fungi ribosomal RNA 488 genes for phylogenetics[END_REF] A total of 39 strains were used for specificity assays of the newly designed primers AtNig1/ 168

AtNig2 by real-time PCR (Table 1). Real-time PCR reactions, with SYBR-Green I and 169

TaqMan probe, were performed using the SYBR-Green I Core Reagents and the TaqMan 170 Core Reagents, respectively (both from Applied Biosystems, Madrid, Spain). Amplification 171 mixtures for real-time PCR reactions with SYBR-Green I, contained in a final volume of 20 172 µL, 1 x PCR Buffer, 200 µM each dATP, dCTP, dGTP and 400 µM dUTP; 1 U of 173 Amperase uracil N-glycosidase; 3 mM MgCl 2 ; 0.9 U of AmpliTaq Gold DNA polymerase, 174 200 nM each primer (AtNig1/ AtNig2) and 5 µL of template DNA (10 ng for specificity 175 assay). Amplification mixtures for real-time PCR reactions with TaqMan probe, contained 176 in a final volume of 20 µL, 1x TaqMan Buffer A, 200 µM each dATP, dCTP, dGTP, and 177 400 µM dUTP; 1 U of Amperase uracil N-glycosidase; 3.5 mM MgCl 2 ; 1 U of AmpliTaq 178 Gold DNA polymerase, 200 nM each primer (AtNig1/ AtNig2), 5 µL of template DNA. 179

The following concentrations of the AN probe were assayed: 50, 100, 150 and 200 nM. 180

Specificity of the real-time PCR assays 243

A new set of specific primers and a probe were designed to target a conserved region in the 244 acyl transferase (AT) domain sequences of PKS genes of all strains belonging to the A. 245 niger aggregate. Specificity was tested by conventional PCR using purified DNA from 47 246 strains (Table 1). The expected 120 bp amplicon was obtained from strains belonging to the 247 species included in the A. niger aggregate (A. awamori, A. foetidus, A. niger, A. tubingensis, 248 A. tubingensis-like, and A. usamii). The 120 bp amplicon was also obtained using DNA 249 from A. lacticofeatus and A. pulverulentus, two OTA-producing species closely related to 250 the A. niger aggregate (Sanson et al. 2004;[START_REF] Perrone | Ochratoxin A 457 production and amplified fragment length polymorphism analysis of Aspergillus 458 carbonarius Aspergillus tubingensis and Aspergillus niger strains isolated from grapes 459 in Italy[END_REF]) (Table 1). Amplification of 251 the 5.8S-ITS region using universal primers its5/its4 was obtained in all strains, thus 252 confirming the DNA suitability when negative amplification results were obtained using the 253 specific primers AtNig1/AtNig2. 254 Specificity of the newly designed primers AtNig1/AtNig2 was also tested by SYBR 255

Green I and TaqMan real-time PCR using 10 ng of template DNA/reaction of 39 strains 256 representing the species included in the study (Table 1). The melting curve analysis showed 257 a Tm value 80.5±0.5 in the A. niger aggregate species. Strains belonging to other genera, 258 showed no melting curve, revealing that no amplification products were obtained. 259 3). For A. 279 carbonarius, C T values obtained by multiplex real-time PCR were slightly higher than those 280 obtained with the uniplex (Table 3). Linear regression analysis of C T values corresponding 281 to A. carbonarius DNA suspensions yielded R 2 values above 0.99 and the slopes were 282 -2.57 with uniplex and -2.56 with multiplex. For A. tubingensis, no differences were 283

Co-amplification using different amounts of target DNA 293

To evaluate the sensitivity of the multiplex real-time PCR, a combination of 10, 10 2 , 10 3 294 and 10 4 genome equivalents of A. carbonarius and A. tubingensis was analyzed (Table 4). 295

Moreover, these combinations were assayed with and without the presence of grape 296 purified DNA. Amplification was observed in all combinations with both SYBR Green and 297 TaqMan. However, when both targets were in very different amounts (10 and 10 4 or 10 2 298 and 10 4 genome equivalents) the one that was in less concentration obtained significantly 299 higher C T value (P<0.01) compared to the corresponding C T when both were at the same 300 concentration (Table 4). On the other hand, C T values obtained in the presence of grape 301 DNA were very similar to those observed when only conidial purified DNA was present, 302 indicating that the grape DNA, extracted as previously described, does not interfere in the 303 The PCR reaction is a well recognized rapid technique widely used for detection of 307 foodborne pathogens. Recently, it is also being applied for detection of toxinogenic 308 microorganisms such us mycotoxin producing fungi. PCR detection of ochratoxigenic fungi 309 has been approached using primers targeted to single species, i.e. A. carbonarius (Mulè et 310 al. 2006;[START_REF] Atoui | Targeting a polyketide synthase gene for Aspergillus 405 carbonarius quantification and ochratoxin A assessment in grapes using real-time PCR[END_REF][START_REF] Selma | Real-time PCR based procedures for 481 detection and quantification of Aspergillus carbonarius in wine grapes[END_REF], A. ochraceus [START_REF] Dao | Two primer pairs to detect OTA producers by PCR 428 method[END_REF], P. nordicum 311 [START_REF] Geisen | Development of a real time PCR system 430 for detection of Penicillium nordicum and for monitoring ochratoxin A production in 431 foods by targeting the ochratoxin poliketide synthase gene[END_REF] or to several species including citrinin producers [START_REF] Dao | Two primer pairs to detect OTA producers by PCR 428 method[END_REF]. 312 [START_REF] Sartori | PCR method for the detection of potential 473 ochratoxin-producing Aspergillus species in coffee beans[END_REF] developed a multiplex conventional PCR for the simultaneous detection 313 of A. carbonarius, A. niger and A. ochraceus in green coffee. In the present study we have 314 developed a rapid, specific and sensitive duplex real-time PCR assay that allows the 315 simultaneous detection of members of the A. niger aggregate and A. carbonarius, which are 316 the main species responsible for OTA contamination in grapes and wine (Abarca et al. 317 2003;[START_REF] Samson | New 469 ochratoxin A or sclerotium producing species in Aspergillus section Nigri[END_REF][START_REF] Battilani | European research on ochratoxin A in grapes and 408 wine[END_REF]Martínez-Culebras & Ramon 2007). 318

With this aim, we combined the previously published A. carbonarius-specific real-time 319 PCR [START_REF] Selma | Real-time PCR based procedures for 481 detection and quantification of Aspergillus carbonarius in wine grapes[END_REF]) with a newly designed real-time PCR targeted to the acyl 320 transferase (AT) domain of a PKS gene of the species belonging to the A. niger aggregate. 321

Grapes isolates belonging to the A. niger aggregate (A. niger, A. tubingensis and A. 322 tubingensis-like) were successfully amplified using the primer pair AtNig1/AtNig2. 323

Additionally, strains belonging to the species A. awamori, A. foetidus and A. usamii, which 324 are also included into the A. niger aggregate, were also amplified by these primers. OTA-325 producing strains of the aforementioned species have commonly been found in different 326 foods and feeds, including grapes [START_REF] Chulze | Occurrence of ochratoxin A in wine and 425 ochratoxigenic mycoflora in grapes and dried vine fruits in South America[END_REF][START_REF] Ponsone | Ochratoxin A and ochratoxigenic 463 Aspergillus species in Argentinean wine grapes cultivated under organic and non-464 organic systems[END_REF]. The newly 327 developed primers also amplified DNA from A. lacticofeatus and A. pulverulentus, two 328 OTA-producing species of the Aspergillus section Nigri closely related to the A. niger 329 aggregate (Sanson et al. 2004;[START_REF] Perrone | Ochratoxin A 457 production and amplified fragment length polymorphism analysis of Aspergillus 458 carbonarius Aspergillus tubingensis and Aspergillus niger strains isolated from grapes 459 in Italy[END_REF]). Nevertheless, these two Aspergillus 330 For the development of a suitable duplex real-time PCR, relative concentration of 334 primers and probes, cycling temperatures and amounts of template DNA and Taq DNA 335 polymerase have to be optimized [START_REF] Markoulatos | Multiplex polymerase chain reaction: A 441 practical approach[END_REF]. In this study, SYBR Green I 336 system, was used for the optimization of the reaction as it is the simplest and least 337 expensive of the real-time PCR methods. By using SYBR Green, amplification products 338 can be identified by their different Tm, by analysing the melting curve of the amplicon 339 [START_REF] Wittwer | Real-time 490 multiplex PCR assays[END_REF]. The presence of a single peak at the corresponding Tm, indicates the 340 specificity of the reaction. In a duplex real-time PCR, both amplicons can be distinguished 341 by differences of at least 1 ºC in Tm [START_REF] Lipsky | DNA melting 438 analysis for detection of single nucleotide polymorphisms[END_REF][START_REF] Ririe | Product differentiation by analysis of DNA 466 melting curves during the polymerase chain reaction[END_REF]). The duplex real-342 time PCR developed in this study yielded two peaks with clearly different Tm values: 80.5 343 ± 0.5 for A. niger aggregate and 83.4 ± 0.4 for A. carbonarius, which confirmed the 344 specificity of the two sets of primers. As a later approach, the duplex assay was adapted to 345 be used in the TaqMan system by adding hybridization probes labeled with two different 346 fluorescent dyes (FAM and VIC). 347

Following optimization of the reaction conditions, the TaqMan duplex real-time PCR 348 developed, was compared with both single real-time PCR reactions using purified DNA. 349 This assay revealed very similar C T values at any A. tubingensis DNA concentration with 350 similar efficiency for uniplex and multiplex assays using as template only 1 target. For A. 351 carbonarius, C T values obtained by multiplex real-time PCR were slightly higher than those 352 obtained with the uniplex but not significant differences in the reaction efficiency were 353 found. Both approaches uniplex and duplex allowed the detection of 30 genome 354 16 equivalents/reaction. Although, the uniplex assay was able to detect as far as 3 genome 355 equivalents/reaction in some replicates, C T values obtained for this concentration were 40 356 or very close to 40 which is at the border line to be considered positive. Thus, the 357 amplification of the two targets is efficient in the presence of the other competing primers 358 and probe keeping the detection limit in 30 genome equivalents/reaction for both of them. 359

These results are in the same range as the detection limit reported for the single detection of 360 A. carbonarius with the TaqMan real-time PCR system developed by [START_REF] Mulè | Development of a quantitative 451 real-time PCR assay for the detection of Aspergillus carbonarius in grapes[END_REF], 361 and about 1 log order lower (more sensitive) than the detection limits reported for the single 362 detection of A. carbonarius with the SYBR-Green I system used by [START_REF] Atoui | Targeting a polyketide synthase gene for Aspergillus 405 carbonarius quantification and ochratoxin A assessment in grapes using real-time PCR[END_REF]. 363

The suitability of this duplex real-time PCR system to detect A. carbonarius and A. 364 niger aggregate strains, was evaluated by co-amplifying both targets present in different 365 proportions using template DNA from both species with and without grape DNA. Both 366 targets were detected in all combinations when using either SYBR Green or TaqMan. 367 However, when both targets are in very different amounts (10 and 10 4 genome 368 equivalents/reaction) the one that is in less concentration renders a C T value very close to 369 40 which indicates the preferential amplification of one of the targets in a multiplex PCR. 370

These results were also obtained when both DNA were present in 10 2 and 10 4 genome 371 equivalents/reaction. This fact can be induced in the presence of very low template 372 concentration, as in this case, due to fluctuation in the interactions of PCR reagents, 373 particularly in the early cycles [START_REF] Mutter | PCR bias in amplification of androgen receptor alleles a 454 trinucleotide repeat marker used in clonality studies[END_REF]. As concentration and C T values do 374 not show a linear correlation when applied to very different amounts of target DNA, 375 quantification would not be possible in these cases. 376

The advantages of the multiplex real-time PCR developed in this study, besides the 377 advantages of the real-time PCR, i.e. highly sensitive and reliable detection technique 378 b Taqman (MGB) probe labeled at the 5´end with VIC ® and at the 3´end with a dark quencher. 527 c Primers and probes designed in a previous study [START_REF] Selma | Real-time PCR based procedures for 481 detection and quantification of Aspergillus carbonarius in wine grapes[END_REF], to target a conserved region in the ß-ketosynthase domain of a polyketido 528 synthase gene (Genbank accession number: AY540952). 529 d Taqman probe labeled at the 5´end with 6-carboxy-fluorescein (FAM) and at the 3´end with 6-carboxy-tetramethyl-rhodamine (TAMRA). 530

(

  Commission regulation No 123/2005 amending Regulation No 67 446/2001 as regards 55

  contribution to OTA contamination in grapes by species belonging to the A. 70 niger aggregate. Therefore, a quick assay capable of quantifying the presence of both A. 71 carbonarius and the A. niger aggregate in grapes would improve OTA risk assessment. 72 Recent advances in DNA-based techniques such as real-time PCR are providing new 73 tools for fungal detection and quantification by detecting and quantifying their DNA. 74

  acyl transferase (AT) domain of the species belonging to the A. niger 93 aggregate. 94

  were performed in 50 µL as final volume, containing 200 ng of DNA, 154 50 mM KCl ,10 mM Tris-HCl, 100 µM (each) dNTP, 1 µM of each primer, 2 mM MgCl 2 155 and 1 U of DNA polymerase (Netzyme, Molecular Netline Bioproducts, N.E.E.D, SL, 156 Valencia, Spain). 157 Amplification conditions were: 35 cycles consisting of 1 min at 95 ºC, 1 min at 52 º C 158 and 1 min at 72 ºC. Reactions were carried out in a GeneAmp PCR System 9700 (PE 159 Applied Biosystems, Norwalk, CT, USA) thermal cycler. Fifteen microlitres of PCR 160 products were electrophoresed through 2 % agarose (Pronadisa, Hispanlab, Madrid, Spain) 161 gel in TAE buffer [40 mM Tris-acetate, pH 7.6 and 1 mM Na acetic acid (EDTA)]. After 162 electrophoresis, gels were stained with ethidium bromide (0.5 mg mL -1 ), and the DNA 163 UV light. Sizes were estimated by comparison with a DNA standard 164 length (GeneRuler TM 100 bp DNA ladder, MBI Fermentans, Vilnius, Lithuania). 165 166 Specificity of the real-time PCR assays 167

  Real-time PCR assays, using either SYBR-Green I or TaqMan probe for fluorescence 181 emission, were carried out in a GeneAmp 5700 Sequence Detection System(PE 182 Biosystems, Foster city, CA, USA) programmed to hold at 50 ºC for 2 min and at 95 ºC for 183 10 min, and to complete 40 cycles of 95 ºC for 15 s and 60 ºC for 1 min. Reactions were 184 done in triplicate. PCR results were given as the increase in the fluorescence signal of the 185 reporter dye detected and visualized by the GeneAmp 5700 SDS software provided with the 186 GeneAmp 5700 SDS (Applied Biosystems). Threshold cycle (C T ) values represent the 187 which an increase in fluorescence, over a defined threshold, first occurred for 188 each amplification plot. 189 190 Multiplex real-time PCR 191 Real-time PCR reactions were performed using both the SYBR-Green I Core Reagents and 192 TaqMan Core Reagents (Applied Biosystems Madrid Spain). Amplification mixtures for 193 Real-time PCR, contained in a final volume of 20 µL, 1x buffer (SYBR-Green I PCR 194 Buffer or TaqMan PCR buffer), 200 µM each dATP, dCTP, dGTP, and 400 µM dUTP; 1 U 195 of Amperase uracil N-glycosidase; 1 U of AmpliTaq Gold DNA polymerase; and 5 µL of 196 template DNA. Concentration of primers, probes and MgCl 2 were optimized for the 197 simultaneous amplification of the two amplicons. The following concentrations were 198 assayed: 3, 3.5, 4 and 5 mM of MgCl 2 ; 100, 200, 300 and 400 nM of primers; 50, 100, 150, 199 and 200 nM of TaqMan probes. Real-time PCR assays were carried out in a GeneAmp 200 5700 Sequence Detection System (PE Biosystems Foster City Calif.) programmed to hold 201 at 50 ºC for 5 min, to hold at 95 ºC for 10 min, and to complete 40 cycles of 95 ºC for 15 s 202 and (60-63 ºC) for 1 min. Several annealing temperatures were assayed to optimize the 203 multiplex amplification. Reactions were done in triplicate. SYBR Green I reactions were 204 carried out in a GeneAmp® 5700 Sequence Detection System (Applied Biosystems). For 205 multiplex real-time PCR reactions using TaqMan probes, an ABI Prism 7000 Sequence 206Detection System (Applied Biosystems) was used. In both cases, PCR results were given as 207 the increase in the fluorescence signal of the reporter dye detected and visualized by the 208 corresponding software, as indicated above. were programmed in order to check the expected amplification product 215 when using SYBR Green I approach. The thermal protocol for dissociation is defined as 15 216 s at 95 ºC, 20 s at 60 ºC and 20 min slow ramp between 60 and 95 ºC, after the real-time 217 PCR program. The data for the dissociation curve is captured during this slow ramp. The 218 melting curve was visualized with the software in the 'Dissociation Window' using the 219 corresponding GeneAmp 5700 SDS software procedure (Applied Biosystems). 220221Sensitivity of the multiplex real-time PCR reaction 222In order to establish detection limits of the multiplex TaqMan real-time PCR, 223 amplifications were carried out for each targeted ochratoxigenic organism using both the 224 uniplex and the multiplex reaction. To that purpose, tenfold serial dilutions of DNA 225 extracted from the reference strains A. carbonarius CBS 11380 and A. tubingensis CBS 226 134.48 were done covering a range from 3 to 3 x 10 5 genome equivalents, that were 227 calculated assuming it to be similar to that of A. niger (4.13×10 -5 ng, for a haploid 228 genome). 229Sensitivity of the multiplex real-time PCR reaction was also analyzed in the presence of 230 grape DNA and different concentrations of fungi DNAs. Grape DNA was obtained from 231 pulsified grape samples as described above (section 2.2.) and tested in triplicate by real-232 time PCR using the A. carbonarius specific primers AcKS10L/ AcKS10R and the A. niger 233 aggregate specific primers AtNig1/ AtNig2, under the amplification conditions established 234 in the study. Grape DNA that tested negative for bothA. carbonarius and A. tubingensis 235 DNA from A. carbonarius CBS 11380 and A. tubingensis CBS 134.48 in 236 different concentrations. Samples were tested in triplicate by real-time PCR and a non-237 template negative control was included in each experiment. Analysis of variance with a 238 significance level of P≤ 0.05 was carried out on these data using SPSS(Windows 2000

  AcKS10L/AckS10R used for the real-time PCR detection of A. 260 carbonarius had previously been demonstrated by[START_REF] Selma | Real-time PCR based procedures for 481 detection and quantification of Aspergillus carbonarius in wine grapes[END_REF]. 261 262 Set up of the multiplex real-time PCR reaction 263 Optimized reaction conditions for the duplex real-time PCR were obtained by using 3.5 264 mM MgCl 2 , 200 nM of A. niger aggregate specific primers and 100 nM of A. carbonarius 265 specific primers. Melting curve analysis of amplicons corresponding to strains belonging to 266 A. niger aggregate and A. carbonarius showed Tm values of 80.5±0.5 and 83.4±0.4, 267 respectively, thus allowing the differentiation between the two targeted organisms (Figure 268 1). For the TaqMan assay, reaction annealing temperature allowing both primers and probes 269 to hybridize was established at 60 ºC. Primer and MgCl 2 concentration was maintained 270 identical to the SYBR Green I reaction. Optimized probe concentration was 200 nM for AN 271 probe targeting A. niger aggregate and 150 nM for AC probe targeting A. carbonarius. 272 273 Sensitivity of the multiplex Taqman real-time PCR compared to uniplex real-time PCR 274 assay 275 Tenfold serial dilutions of DNA extracted from the reference strains A. carbonarius CBS 276 11380 and A. tubingensis CBS 134.48 covering 6 log orders, were used for multiplex and 277 uniplex TaqMan real-time PCR assays in order to establish detection limits of the multiplex 278 real-time PCR reaction compared to the uniplex real-time PCR (Table

  C T values obtained by multiplex real-time PCR and uniplex real-time 284 PCR. At the lowest concentration tested (3 genome equivalents/reaction), a slight 285 amplification signal was obtained in 1 out of 3 replicates with the uniplex reaction and no 286 amplification was observed with the multiplex real-time PCR. Linear regression analysis of 287 C T values corresponding to A. tubingensis DNA suspensions yielded R 2 values above 0.99 288 and the slopes were -2.73 with uniplex and -2.67 with multiplex. These results indicate no 289 differences in sensitivity when using either the two sets of primers and probes, in separate, 290 or in the same reaction. 291 292

  been isolated from grapes. Negative results with DNA from other 331 confirmed the specificity of the newly designed primers. 333

Figure 1 .A

 1 Figure legends 496

  Fig 1. 551

Table I .

 I Fungal strains used for specificity assay of primers AtNig1/ AtNig2 and results 517 of specificity by conventional PCR and real-time PCR.

	518
	Species	Strain	Source of isolation	OTA b	PCR
	Aspergillus awamori Aspergillus carbonarius Aspergillus costariciensis Aspergillus foetidus Aspergillus heteromorphus CBS117.55 a CECT 2907 a CBS 101701 a CBS 113.80 a CBS111.26 a W04-20 a W04-30 a W04-32 a W04-35 a W04-40 a CBS 115574 a CBS 101708 CBS565.65 a Aspergillus homomorphus CBS101889 a Aspergillus japonicus CBS114.51 a Aspergillus lacticofeatus T CBS101883 Ta Aspergillus níger CECT 2090 a CECT 2091 W04-19 W04-136 a W04-140 a W04-150 a Aspergillus ochraceus CECT 2948 a CBS 236.67 a Aspergillus piperis CBS 112811 T F o r P e e r R e v i e w Bran, USA + Unknown substratum, Japan + Cocoa, Nigeria ND Unknown substratum ND Wine grape, Spain + Wine grape, Spain + Wine grape, Spain + Wine grape, Spain + Wine grape, Spain + Soil, Costa Rica -Unknown substratum + Unknown substratum, Japan + -Trichophyton contaminated culture, Brazil -Soil, Israel -Unknown substratum -Coffee, Venezuela + Unknown substratum ND Soil, Canada ND Wine grape, Spain + Wine grape, Spain + Wine grape, Spain + Wine grape, Spain + Unknown substratum + Unknown substratum + Black pepper, Denmark -	+ + --------+ + ---+ + + + + + + ---O n l y
	Aspergillus pulverulentus	CBS 558.65 a	Unknown substratum	+	+
	Aspergillus tubingensis	CBS 136.52 CBS134.48 a W04-12 a	Kuro-koji, Japan Unknown substratum Wine grape, Spain	-ND +	+ + +
			W04-28	Wine grape, Spain	+	+
	W04-53 W04-57 a W04-109 a W04-118 a W04-146 a Aspergillus tubingensis-like W04-17 a W04-22 a W04-67 a W04-77 a W04-79 a W04-132 a	Wine grape, Spain Wine grape, Spain Wine grape, Spain Wine grape, Spain Wine grape, Spain Wine grape, Spain Wine grape, Spain Wine grape, Spain Wine grape, Spain Wine grape, Spain Wine grape, Spain	ND ND ND ND ND + + ND ND ND ND	+ + + + + + + + + + +
	Aspergillus usamii	CBS 101700 a	Unknown substratum	+	+
	Botrytis cinerea	W04-186 a	Wine grape, Spain	-	-
	Cladosporium spp.	W04-122 a	Wine grape, Spain	-	--
	Fusarium spp.	W04-101 a	Wine grape, Spain	-	--
	Neopetromyces muricatus	CBS 113177	Unknown substratum, USA	+	-
	Penicillium spp.	W04-28 a	Wine grape, Spain	-	-
	519	ND: OTA production was not determined. W04: Strains isolated from Spanish vineyards. CBS: Centralbureau voor
	521 522	Culebras and Ramón 2007, Martínez-Culebras et al. 2008)
	523
	524

Schimmelcultures. T: Type strain. CECT: Spanish Type Culture Collection. ª Strains tested by SYBR Green I and 520 TaqMan RTi-PCR using AtNig1/ AtNig2 primers. b OTA production was tested in previous studies (Martínez-

Table II .

 II Primers and probes used in this study. 525

		Size Oligonucleotide sequence	Tm Location
	AtNig1	22	5´-GAC TGA GCC CAG ATG ACC TAC A-3´	63.9	124-145 a
	AtNig2	18	5´-CGC TGT CGC CGG ATA CTG-3´	66.4	244 to 227	a
	AN probe b 31	5´-VIC-TTG ACT ATT GCA TGT TTT AAT AGC CCR AAG AAC C-MGB-3´ 67.0	177 to 147	a
	AcKS10R 22	5´-CCC TGA TCC TCG TAT GAT AGC G-3´	65.1	362 to 340	c
	AcKS10L 22	5´-CCG GCC TTA GAT TTC TCT CAC C-3´	65.4	201-223 c
	AC probe d 23	5´-FAM-AGA ACG CTG ATG GGT ATG CGC GG-TAMRA-3´	70.0	275 to 252 c

a Primers and probes designed in this study, to target a conserved region in the acyl transferase domain of polyketido synthase gene. 526

Table III .

 III Comparison of C T values obtained by TaqMan real-time PCR uniplex and multiplex assays using as template only 1 target, purified 531 DNA of A. carbonarius CBS 113.80 or A. tubingensis CBS 134.48 from 3 x 10 5 to 3 equivalents/reaction. 532 Calculated assuming that genomic DNA weight of A. carbonarius CBS 113.80 and A. tubingensis CBS 134.48 is similar to that of A. niger (4.13×10 -5 ng for 533 a haploid genome). b C T values (mean ± SD) corresponding to three replicates. c Negative, no amplification. Standard curves obtained from genomic DNA serial 534 dilutions: d y= -2.57x +40.05; e y= -2.56+40.69; f y=-2.73 x +42.27; g y= -2.67 x +42.04. h C T value corresponding to the replicate out of 3 that showed

	Page 25 of 27			Food Additives and Contaminants
		Genome equivalents/reaction a	A. carbonarius	A. tubingensis
							Formatted: Superscript
				Uniplex d	Multiplex e	Uniplex f	Multiplex g	Formatted: Superscript
							Formatted: Superscript
		3.0 x 10 5		26.32 ± 0.39 b	27.49 ± 0.60	27.13 ± 0.07 b	27.67 ± 0.09	Formatted: Superscript
		1.5 x 10 5		27.00 ± 0.30	27.81 ± 0.49	27.24 ± 0.08	27.66 ± 0.01
		3.0 x 10 4 3.0 x 10 3	F o r	27.80 ± 0.19 30.82 ± 0.48	28.41 ± 0.48 30.29 ± 0.21	29.73 ± 0.26 33.79 ± 0.64	29.73 ± 0.73 33.13 ± 0.23
		3.0 x 10 2	34.09 ± 0.49 P	34.12 ± 0.30	36.20 ± 0.24	35.95 ± 0.82
		30 3	36.56 ± 0.50 e 39.25 ± 0.69 e r	37.81 ± 1.20 (-) c	39.09 ± 0.07 39.37 h	38.59 ± 0.52 (-) c	Deleted: 40.00 ± 0.00 c Deleted: 79 ± 0.36
	535 536	amplification.		R e		Formatted: Superscript Deleted: CT ≥ 40 n
					v i e
					w
					O n l
						y

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Table IV .

 IV Co-amplification of different amounts of purified DNA fromA. carbonarius 537 CBS 113.80 and A. tubingensis CBS 134.48 in the presence of grape DNA. Genome equivalents/reaction. Genomic DNA weight of A. carbonarius CBS 113.80 539 and A. tubingensis CBS 134.48 was calculated assuming them to be similar to that of A. 540 niger (4.13×10 -5 ng for a haploid genome). 541

	538
		DNA a		SYBRGreen		TaqMan b
		A. carbonarius A. tubingensis	A. carbonarius A. tubingensis	A. carbonarius A. tubingensis
		10 4	10	+	+	24.30 ± 0.71 36.34 ± 0.63
	Without grape DNA	10 4 10 4 10 4 10 10 2 10 3	10 2 10 3 10 4 10 4 10 4 10 4	+ + + + + +	+ + + + + +	23.20 ± 0.17 33.36 ± 1.70 22.90 ± 0.17 24.90 ± 0.21 22.92 ± 0.26 21.71 ± 0.87 38.93 ± 0.12 21.86 ± 0.14 35.71 ± 1.30 22.04 ± 0.47 27.20 ± 0.26 21.94 ± 0.19
		10 2	10 2	+	+	29.97 ± 0.12 28.51 ± 0.07
		10 4	10	+	+	23.12 ± 0.18 30.13 ± 0.20
	With grape DNA	10 4 10 4 10 4 10 10 2 10 3	10 2 10 3 10 4 10 4 10 4 10 4	+ + + + + +	+ + + + + +	22.98 ± 0.12 28.92 ± 0.64 22.79 ± 0.16 24.91 ± 0.72 23.40 ± 0.39 22.39 ± 0.25 38.07 ± 0.56 22.13 ± 0.03 33.09 ± 1.40 22.37 ± 0.06 27.26 ± 0.38 22.44 ± 0.17
		10 2	10 2	+	+	30.87 ± 0.21 30.52 ± 1.30

a

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Acknowledgements

387

The authors are grateful to Spanish CICYT (Comisión Interministerial de Ciencia y 388 Tecnología) projects AGL2005-00707 and AGL2004-03060 for financial support. M.V. S. 389 is grateful to the CSIC (Spanish National Research Council) for an I3P contract (I3PDR-7-390 01). P.V.M.C. is supported by a Ramón y Cajal research contract, cofinanced by Spanish 391

Government and the University of Valencia. 392 393


Mª L Copete

Luisa

A Zalacain

C Lorenzo

J M Carot

Mª D Esteve

Mª Climent

Salinas

OCCURRENCE OF HALOANISOLE AND HALOPHENOL 1 CONTAMINATION IN AGED RED WINES 2 3 4

Keywords: Pesticides -organochlorine Contamination, Haloanisoles, Halophenols, Aged red wine 30

This exhaustive study is the first to be carried out on the incidence of halophenols and 16 haloanisoles in aged red wines, not only in terms of trichloroanisole. Nine hundred and sixty-17 six red wines of different ageing times (6, 12 and 24 months in oak barrels) and different 18 Spanish production areas were analysed by stir bar sorptive extraction followed by GC/MS. 19

From the total sampling, 155 (16.1%) wines were contaminated with one or several 20 compounds, with 7.6% of these corresponding to the aged-12 wine category, 6.9% to the 21 aged-6 group and the rest to the aged-24 wines (1.5%). The most abundant compounds 22 causing taint were 2, 3,4,6-tetrachloroanisole and 2,4,6-trichloroanisol (6.8 and 5.3 %, 23 respectively). No 2,4,6-tribromophenol was found in any of the samples. The contamination 24 with halo-compounds was highest in the samples from the South-West of Spain, followed by 25 those from the North. The mean concentration found for all compounds are always higher 26 than their respective olfactory threshold, but neither of these halo compounds represent a 27 health hazard to human subjects through the consumption of commercial red aged wines.

Introduction 1 2 Musty taint, traditionally known as "cork taint", is a serious problem for both wine and cork 3 industries worldwide. This flavour-damaging effect is usually perceived as a mouldy, musty 4 and/or earthy aroma that may mask the natural wine aroma and lessen its quality (Amon et al., 5 1989;Butzke et al., 1999;[START_REF] Fuller | Cork taint: closing in on an industry problem[END_REF][START_REF] Peña-Neira | Presence of cork-taint responsible compounds in wines and their cork stoppers[END_REF]Mazzoleni and Maggi et al., 6 2007). Although different compounds have been identified in relation to this alteration 7 (guaiacol, geosmine or 2-metilisoborneol among others) [START_REF] Maga | Simple phenol and phenolic compounds in food flavour[END_REF], most authors agree 8 that halophenols and haloanisoles, particularly chloroanisoles, are the primary compounds 9 be responsible for the "cork taint" when insufficient amounts of TCA or other chloroanisoles 12 are detected in wines [START_REF] Chatonnet | Identification and responsibility of 8 2,4,6-tribromoanisole in musty, corked odors in wine[END_REF]. [START_REF] Fuller | Cork taint: closing in on an industry problem[END_REF] 14 Traditionally, and erroneously, the wine contamination with this off-flavour has been 15 associated with the cork, and therefore the inappropriate used of the term "cork taint" has 16 contributed to the spreading of the idea that contamination with chloroanisoles is always 17 attributed to the cork stopper. Scientific data have shown that the true origin of the wine 18 contamination by halophenols and haloanisoles is in fact a problem of environmental 19 contamination. Blaming the cork stopper almost exclusively is too simplistic as there are 20 many different sources of contamination. In fact, in some cellars, it is possible to detect 21 contaminated wines that have never been in contact with cork, thus attributing the problem to 22 other enological products that have been in contact with chlorine derivatives used as 23 pesticides or cleaning products such as hypochlorite-based disinfectants (Chatonnet et al. 24 2004). These volatiles are easily transmitted through the air, and show a great capability for 25 adhering and contaminating wood, cork and many other materials (plastic polymers, silicons, 26 cardboard and paper, etc). Most studies also deal with chloroanisoles, especially TCA, due to 27 their low olfactory thresholds, but chlorophenols are as important as they are considered their 28 the European Union several years ago. However, they can persist in the ecosystems for a very 2 long time [START_REF] Rubio-Coque | Causes and origins of 22 wine contamination by haloanisoles (chloroanisoles and bromoanisoles)[END_REF]. This problem also affects human health since the 3 precursors are considered as highly toxic [START_REF] Armstrong | 2,4,6-trichlorophenol (TCP) induces 29 chromosome breakage and aneuploidy in vitro[END_REF][START_REF] Fahrig | Genetic activity of chlorophenols and chlorophenol 12 impurities[END_REF]Jansson 4 and Jansson, 1992;[START_REF] Hattula | Mutagenesis of mammalian cells in culture by chlorophenols, 16 chlorocatechols and chloroguaiacols[END_REF][START_REF] Mcgregor | 8 Responses of the L5178Y tk+/tk-mouse lymphoma cell forward mutation assay: III. 72 9 coded chemicals[END_REF][START_REF] Ono | Genotoxic evaluation on aromatic organochlorine 11 compounds by using umu test[END_REF]. 5

Yet, international legislation only limits the content of some halophenols in drinking water (5 6 µg/L in TCP) [START_REF]Integrated Risk Information System[END_REF], with nothing being said about haloanisoles. Soleas et al. (2002) 7 carried out a cytotoxicity study using TCA and TCP standard solutions up to a concentration 8 of 500 µg/L, with neither TCA nor TCP adversely affecting the viability of any of the cells 9 lines tested. 10 11 Despite being a great cause for concern for the wineries all around the world, there are many 12 discrepancies about its real incidence, and the quantification of the economic losses produced 13 by the contamination from these compounds. Most studies refer to TCA, and percentages 14 greater that the 7% have been not shown (Butzke et al., 1999;[START_REF] Fuller | Cork taint: closing in on an industry problem[END_REF]Lee and Simpson, 15 1993;[START_REF] Pollnitz | The analysis 16 of 2,4,6-trichloroanisole and other chloroanisoles in tainted wines and corks[END_REF][START_REF] Soleas | Method for the gas chromatographic assay 27 with mass selective detection of trichloro compounds in corks and wines applied to 28 elucidate the potential cause of cork taint[END_REF]. In the most exhaustive study, carried out by 16 [START_REF] Soleas | Method for the gas chromatographic assay 27 with mass selective detection of trichloro compounds in corks and wines applied to 28 elucidate the potential cause of cork taint[END_REF], a panel of experts analysed more than 2,400 different wines from several 17 countries. The overall incidence of "cork taint", only measured in terms of TCA, was 6.1%, 18 but those wines closed with composite corks demonstrated an incidence of 31.9%. 19 Differences were also observed between white and red wines with an incidence of 8.3% and 20 4.2%, respectively. Among red wines, the highest incidence was observed for Portugal (6.7%) 21 and Spain (6.5%), although only the 12.6% of the total sampling came from those two 22 countries. 23 24 For all these reasons, the occurrence of halophenols and haloanisoles, not only TCA, in nine-25 hundred and sixty-six Spanish aged red wines has been analysed using SBSE-GC-MS. The 26 presence of the target compounds has been related to the different wine production areas and 27 other oenological parameters. Additionally, an estimation of halophenol and haloanisole 28 ingestion by Spanish red wine consumers has been carried out. 29 Solvents: ethanol (analytical-reagent grade) was obtained from Merk (Damstard, Germany), 7 while water was purified through a Milli-Q system (Millipore, Bedfords, MA, USA). 8 Synthetic wine samples were prepared by an ethanol solution at 12 % (v/v) to which 5 g/l 9 tartaric acid were added. Solution pH was adjusted to 3.6 with 1 M sodium hydroxide 10 (Panreac, Barcelona, Spain). 11 12

30

MATERIAL AND METHODS 31

Chemicals and reagents

Classical Oenological parameter analysis 13

The classic analyses of must and wines were performed according to the official methods 14 established by the [START_REF] Ecc | Commission Regulation VO 2676/90 concerning the establishment of common 10 analytical methods in the sector of wine[END_REF]. The following parameters were analysed: pH, alcohol degree, 15 and total acidity. 16 17

Stir Bar Sorptive Extraction (SBSE) 18

Compounds were extracted by introducing the polydimethylsiloxane coated stir bar (0.5 mm 19 film thickness, 10 mm length, Twister, Gerstel, Mülheim and der Ruhr, Germany) into 10 ml 20 of sample (either commercial wine or synthetic wine solution), to which 100 µl of internal 21 standard γ-hexalactone solution at 6 µl/l in absolute ethanol was added. Samples were stirred 22 at 700 rpm at room temperature for 60 min. The stir bar was then removed from the sample, 23 rinsed with distilled water and dried with a cellulose tissue, and later transferred into a 24 thermal desorption tube for GC/MS analysis [START_REF] Zalacain | Stir bar sorptive extraction 32 for the analysis of wine cork taint[END_REF]. 25

26

TD-GC/MS analysis 27

The thermal desorption equipment (ATD 400 of Perkin-Elmer, Norwalk, USA) was coupled 28 to the gas chromatograph. The stir bar was introduced into the thermal desorption tube and 29 the volatile compounds were desorbed from the stir bar at the following conditions: oven 30 temperature at 330 ºC; desorption time, 4 min; cold trap temperature, -30 ºC; helium inlet 31 flow 45 ml/min. The compounds were transferred into the Hewlett-Packard 6890 gas thickness) (SGE, Ringwood, Australia). The chromatographic program was set at 50 ºC (held 3 for 5 min), raised to 180 ºC at 2.5 ºC/min (held for 2 min) and to 230 ºC (5 ºC/min) and held 4 for 20 min. For mass spectrometry analysis, electron impact mode (EI) at 70 eV was used. 5

The mass range varied from 35 to 500 u and the detector temperature was 150 ºC. 6

Identification was carried out by comparing with their respective standards and using the 7 NIST library. Quantification was carried out by using the extracted ion mode. with their 8 respective m/z, and it was based on the calibration curves of standards in the synthetic wines 9 [START_REF] Zalacain | Stir bar sorptive extraction 32 for the analysis of wine cork taint[END_REF]. Triplicate analysis was carried out for all wines. 10 11

Wine Samples 12

One of the most tedious tasks of this study was the selection of samples, as the authors wanted 13 to have the widest and most realistic wine sample distribution from the consumer point of 14 time in oak barrels of 6, 12 and 24 months, all of which require another period in bottle before 1 being eligible for sale at 18, 24 and 36 months, respectively. The total number of samples 2 analysed were 966 quality Spanish aged red wines from three different categories named as 3 aged-6, aged-12 and aged-24 (Table 1). 4 5

Statistical analysis 6

Data was processed by the Answer Tree 3.0, SPSS 14 and Unscrambler 9.0 using the CART 7 method (Classification And Regression Trees) which is an binary algorithm developed by 8 [START_REF] Breiman | Classification and regression trees. 31 Belmont, California: Wadsworth. 32 phase microextraction in combination with GC/MS-SIM[END_REF]. CART divided the data into two subsets, so cases falling within each 9 of the subsets are more homogeneous than in the previous subset. It is a recursive process that 10 repeats itself until reaching the criterion of homogeneity or another criterion for stopping. The 11 same predicting variables can be used several times at different levels of the tree. 12 13 RESULTS AND DISCUSSION 14 15 Due to the discrepancies found about the impact of halophenols and haloanisoles 16 contamination in quality wines, 966 different aged red wines were analysed (Table 1). It is 17 important to point out that this study is not only concerned with TCA as most studies are, but 18 with the most important halophenols and haloanisoles related to this wine off-flavour defect 19 [START_REF] Maarse | Halogenated phenols and chloroanisoles: 27 occurrence, formation and prevention[END_REF][START_REF] Tanner | Zur analytischen differenzierung von muffon und 30 korkgeschmack in wein[END_REF]. The study has revealed that 155 wine samples were 20 contaminated with one or several compounds, which means the 16.1% of the total sampling. 21

Of these 155 tainted cases, the 7.6% correspond to the aged-12 wines category, the 6.9% were 22 aged-6 and the rest were aged-24 wines (1.5%). This tendency is not related with the 23 wineries' belief that the longer the time in the oak barrels, the higher the possibility of 24 detecting such off-flavours (personal communications). No conclusions can be reached when 25 the different aged categories of contaminated wines were compared with the geographical 26 production areas (Table 1), as areas 1, 3 and 4 showed that aged-6 red wines where more 27 contaminated than the other categories and in areas 2 and 6 contamination was associated 28 with the aged-12 wines and aged-6 red wines. Without distinction of wine categories, area 3 is 29 the one with the highest incidence of tainting compounds (37.5%), followed by areas 6 30 (18.2%) and 1 (16.1%). 31 As it can be observed in Table 2, from the seven target compounds analysed, TCA and TeCA 1 were the most abundant, 5.3 % and 6.8 % respectively, followed by TCP. The higher 2 percentage of TeCA and TCP is quite surprising, as both are potential precursors of TCA 3 although conversion takes place through different pathways [START_REF] Maarse | Halogenated phenols and chloroanisoles: 27 occurrence, formation and prevention[END_REF], Tanner et 4 al., 1981). The higher occurrence of the tainting compounds was observed in aged-12 red 5 wine (Table 3). Looking at Table 2, it is worthy of mention that in area 3, the most 6 contaminated area, no TCA or TeCA was detected, but PCA (12.5%) and specially TCP 7 (25%) were found. Those wines may be not be rejected by wine consumers for the moment as 8 TCP and PCA olfactory thresholds are higher than TCA, but their evolution is of great 9 importance in terms of TCP conversion into TCA. Area 6 has a 18.2% of their total wine 10 sampling, with TeCA being the most abundant compound (9.3%) followed by TCA (5.9%), 11 and with PCA, TCP and TBA (Table 2) showing lower values. The 16.1% of the wines 12 analysed for area 1 have shown TCP as the one with the highest percentage (8.8%), whereas 13 the remaining compounds (TCA, TeCA, PCA and TBA) do not surpass the 3.6%. In area 4, 14 although the percentage of contamination is lower (11.5%) than area 6, the type of 15 compounds found and the frequency at which they are detected are similar. In this case, TeCA 16 is the most abundant haloanisole, followed by TCA, while under 4% of the wines analysed 17 are contaminated with the other tainting compounds. Lastly, in area 2 showed a contamination 18 of 9.8%, with TCA the most abundant (4.5%). Below 3%, TeCA, PCA and TCP are detected. [START_REF]Integrated Risk Information System[END_REF] Special mention should be made for TBA and TBP contamination, as Chatonnet et al., (2004) 20 indicated that both compounds seem mainly to derive mainly from environmental pollution in 21 wineries. TBP derivatives are often used as flame retardants in a broad range of materials, 22 thus raising the risk of pollution. In this study, TBP has not been found in any of the wines 23 analysed, but TBA has always been detected at a percentage lower than 3%. 24 25 A uniform contamination distribution in terms of geographical areas can be observed, as areas 26 1 and 6 are grouped within the northern zone of Spain followed by areas 2 and 4 which 27 corresponded with the east-central zone of the Spanish mainland. It is not possible to affirm 28 that cork stoppers are the only elements responsible for such contamination, as the 29 contamination pattern found within this sampling in terms of wine production areas is not in 30 accordance with such an affirmation. This does not mean that wineries from the north of 31 Spain use stoppers of poorer quality than, for example, the centre-east. Such taint distribution, 32 south-west of Spain (area 3) > northern (area 1 and 6) > centre-east (areas 2 and 4) may be 33 attributed to the effect of the environmental conditions on the microorganism propagation 34 Evidently it is not possible to conclude that the humidity conditions are the only responsible 6 for the higher contamination, but wooden deposit use for winemaking in some cellars of these 7 areas may be important on this occurrence. 8 9

In addition, the mean concentration of the compounds found in the contaminated wines are 10 higher than their respective olfactory thresholds (Table 5), which means that consumers will 11 perceived them with clarity in taste and smell, and therefore reject those wines. Such high 12 concentrations suggest that cork stoppers are not the only factor responsible for this wine off-13 flavour, along with the fact that cork factories have diminished TCA by about 75% in recent 14 years, a consequence of the many controls adapted to avoid such contamination (Rubio-15 [START_REF] Rubio-Coque | Causes and origins of 22 wine contamination by haloanisoles (chloroanisoles and bromoanisoles)[END_REF]. Other studies reveal as well that cork stoppers can only contaminate the 16 wine when the haloanisoles are located on the surface in contact with the wine (Pollintz et al., 17 1996). However, [START_REF] Capone | 3 Absortion of chloroanisoles from wine by corks and by other materials[END_REF][START_REF] Capone | Permeation of 2,4,6-trichloroaniles 6 through corks closures in wine bottles[END_REF] goes further by stating that only occasionally 18 does more than the 10% of the TCA from the cork leach into the bottled wine and, in most 19 cases, TCA cork does not leach into wine at all. In this way, the concentration found in the 20 wines is again too high to be transferred from the cork stopper (Table 5). 21 22 Consumers are an important part of this problem. In 2004/05 red wine from OD was bought 23 in 8,191,603 Spanish households, i.e. 55.5% of the total national, with areas 4 and 6 having 24 the highest consumption percentage, 24.4 and 54.1% respectively (Table 6). For each 25 purchase, 1.8 l of wine per person/month is calculated [START_REF] Mapa | Distribución, Consumo y Comercialización de vinos tintos VCPRD[END_REF]. The average size of a 26 Spanish household is 2.9 persons and, when considering the average consumption of red wine 27 with OD and the average number of occupants per home, a common wine consumer will 28 drink an average of 8.8 l / year. If this consumption data is related to the occurrence of 29 halophenols and haloanisoles in aged red wines presented in Table 1 and considering the only 30 toxicity normative available for TCP, 5 µg L -1 in drinking water for TCP is acceptable, the 31 mean concentration of tainting compounds found in those wines will never be a problem for 32 quality red wine consumers, even if they are unfortunate enough to only buy contaminated 33 wines from areas 1, 3 and 6. If these results are compared with a previous study done by In order to get more information about the incidence on this problem, another statistical 8 analysis was carried out including decision trees which related the percentage of contaminated 9 wines with the areas studied, together with the aged wine categories (Figure 1). The first 10 division is carried out according to the wine age category, finding significant differences 11 between the aged-12 wines (20.7 %) and the other two aged wine categories (aged-6 and 12 aged-24 wines, 13.4 %). Looking first at aged-12 wines, there is a variability which takes into 13 account the geographical wine areas, where areas 1 and 6 (northern Spain) were the most 14 contaminated (23.5 %) followed by 12.9 % in the remaining wine making areas. In relation to 15 the other group of aged wines (6 and 24-aged), the statistical analysis revealed significant 16 differences between the area 3 and the other areas studied, confirming the early data 17 discussed. In fact, the 50% of the analysed wines from area 3 have any of the haloanisoles and 18 halophenols studied, while this percentage is not higher than the 12.7% for the rest of the 19 areas. 20 21 Classical wine parameters such as pH, total acidity and alcoholic degree were used within the 22 decision trees as differentiating variables for contaminated wines in order to obtain more 23 information about their possible effect on the wines. As there was too much data to process 24 for each parameter, four sub-groups have been differentiated according to: alcohol (11-11.9%, 25 12-12.9%, 13-13.9% and 14-14.9%); pH (<3.2, 3.2-3.4, 3.4-3.6, > 3.6) and total acidity 26 (between 4-4.9, 5-5.9, 6-6.9 and 7-7.9 g/l of tartaric acid). But no correlation was found and 27 therefore no decision tree was shown. The same results were obtained by other authors when 28 the extraction of TCA at different alcohol degrees was followed, but no conclusions could be 29 obtained as the opposing effects of increased TCA extraction and loss of TCA volatility at 30 high ethanol levels tend to cancel each other out [START_REF] Hervé | TCA in corks, cork soaks and bottled wine[END_REF]. This same effect is 31 likely to hold for sensory analysis as well, as [START_REF] Mazzoleni | Effect of wine style on the perception of 2,4,6-trichloroanisole, 6 a compound related to cork taint in wine[END_REF] carried out an 32 exhaustive sensory analysis and confirm that the detection level of TCA in red wines cannot 33 This exhaustive study is the first to be carried out on the incidence of all halophenols and 5 haloanisoles in red aged wines, and not only in terms of TCA. The study has revealed that 6 16.1% of the total wine sampling was contaminated with one or several compounds, with the 7 most contaminated wines being those aged for at least 12 months, followed by aged-6 and 8 aged-24 months wines. Although the most abundant tainting compounds are TeCA and TCA, 9 special attention should be given to the high concentrations of TCP, precursor of TCA. Due to 10 the mean concentration of tainting compounds and the geographical areas distribution, the 11 cork stopper is not the only factor responsible for such taint incidence since the south-western 12 and northern areas of the Spanish mainland are the most contaminated, coinciding with the 13 areas with the highest humidity conditions, ideal conditions for microorganism propagation. 14 However, other sources of contaminations to be taking into account in these areas can be the 15 wooden materials used during winemaking. Despite their possible economic damage to the 16 wine industry, even the highest concentration encountered in commercial aged red wines is 17 several orders of magnitude below the levels that may be harmful to human health. 18

F

  responsible for this problem (Butzke et al., 1999; Chatonnet et al., 2004; Silva-Pereira et al., 10 2000; Rubio-Coque et al. 2006). Other compounds such as 2,4,6-tribromoanisole (TBA) can 11

  precursors. Chlorophenols may originate in several ways, the most accepted hypothesis being 29 the O-methylation reaction by different microorganisms (especially fungi) (Álvarez-30 Rodriguez et al., 2002; Riu et al., 2002; Maggi et al., 2008). Many different microbes, e.g. 31 common moulds such as Penicillium, Aspergillus, Trichoderma and even Botrytis cinerea can 32 generate haloanisoles from halophenols[START_REF] Lee | Microbiology and chemistry of cork taints in wine[END_REF] Maggi et al., 2008). The 33 most used halophenols have been especially pentachlorophenol (PCP) and 2,4,6-), which have been used as pesticides, although they were forbidden in 1

  an Hewlett-Packard mass detector (Palo Alto, USA) with a fused 1 silica capillary column (BP21 stationary phase 50 m length, 0.22 mm i.d., and 0.25 µm film 2

  view. A planned and randomised sampling taking into account the information provided by 15 the Spanish Ministry of Agriculture, Fisheries and Food (MAPA, 2004) on domestic trade and 16 wine production volume which affirmed that 95% of the Spanish Origin Designations (OD) 17 produced more than 30,000 hl, was used for experimental sampling design. Wine selection 18 was carried out in local supermarkets of 8 Spanish cities according to the data obtained, where 19 four OD (Rioja, Mancha, Ribera del Duero and Valdepeñas) represented approximately 72% 20 of all commercialized red wines. The selection of the other Spanish OD for this study was 21 based on the information given by the MAPA, although an effort was made to include the 22 different geographical wine production areas. Due to the great number of samples and the 23 exhaustive consumption study of red wines obtained through ACNielsen consulting, all OD 24 have been grouped according to the areas (ACNielsen, 2004) defined as follows: area 1: 25 Priorato, Terra Alta, Costers del Segre, Cariñena, Penedés and Somontano; area 2: Jumilla, 26 Valencia, Utiel -Requena ; area 3: Guadiana; area 4: Mancha, Valdepeñas, Toro and Vinos de 27 Madrid; area 6: Ribera del Duero, Navarra and Rioja. No wines from area 5 were bought as 28 mainly white wines are produced. 29 30For this study, only aged red wines of the highest quality have been chosen. According to the 31 Spanish legislation and in agreement with the Regulatory Council for Origin Appellations, 32 there are three oak-aged red wines categories. These categories establish a minimum period of 33

  to polluted zones of halophenols in the wineries (Rubio-Coque et al., 1 2006). The westen (area 3) and northern (areas 1 and 6) parts of Spain are characterized by 2 their high humidity conditions (MAPA, 2004) (Table 4). The size of the microbial population 3 significantly increases with humidity (Alvarez-Rodriguez et al. 2002), and may justify why 4 these areas are the most contaminated of course if enough sources of precursors are present. 5

  [START_REF] Soleas | Method for the gas chromatographic assay 27 with mass selective detection of trichloro compounds in corks and wines applied to 28 elucidate the potential cause of cork taint[END_REF] where the concentration limits are fixed at 500 µg/L (TCA and TCP), 1 then we could conclude that neither of these halo compounds represent a health hazard to 2 human subjects through the consumption of commercial aged red wines. It is important to 3 point out that no other toxicity information has been found in relation to the other halophenols 4 and haloanisoles in any other matrixes, and of course not in wines, leaving an via open for 5 future research. 6 7

3

 3 analytical parameters such as character ethanol, sugar content, pH, and 1 total acidity, whereas a positive differentiation can be carried out with white wines. 2 Conclusions 4

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  Decision tree which related the percentage of contaminated wines with the studied areas and the wine aged categories.

	1		Contaminated wines
			Node 0
			Category	%	n
			no	83.95 811
			yes	16.05 155
			Total (100.00) 966
			Aged Wine Category
			Improvement=0.0025
		Aged-12			Aged-6; Aged-24
		Node 1				Node 2
	Category %	n		Category %	n
	no	79.26 279		no	86.64 532
	yes 20.74	73		yes	13.36	82
	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 F 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 Total (63.56) 614 Category no yes Total Node 6 % 50.00 6 n 50.00 6 (1.24) 12 Category % n no 87.38 526 yes 12.62 76 Total (62.32) 602 Node 5 Total (36.44) 352 Category % n no 87.10 81 yes 12.90 12 Total (9.63) 93 Node 4 Category % n no 76.45 198 yes 23.55 61 Total (26.81) 259 Node 3 Category % n no 80.85 38 yes 19.15 9 Total (4.87) 47 Node 16 % n 75.47 160 24.53 52 Total (21.95) 212 Category no yes Node 15 Areas Improvement=0.0034 AR3 AR6;AR4;AR2;AR1 Areas Improvement=0.0016 AR4;AR2;AR3 AR6;AR1 Areas Improvement=0.0002 AR1 AR6 o r P e e r R e v i e Figure 1.-F w
						O n l O n l O n l O n l O n l
						y y y y y
						13

Table 1 .

 1 -Distribution of aged red wine sampling and the percentage of contamination according to the aged wine category and geographical production area.

		Number of analysed wines
		Aged-6	Aged-12	Aged-24	Total
	AREA 1	81	47	9	137
	AREA 2	67	37	8	112
	AREA 3	12	4	0	16
	AREA 4	100	52	22	174
	AREA 6	243	212	72	527
	Total	503	352	111	966
		% of Contaminated Wines
		Aged-6	Aged-12	Aged-24	Total
	AREA 1	8.0	6.6	1.5	16.1
	AREA 2	4.5	5.4	0	9.8
	AREA 3	37.5	0	0	37.5
	AREA 4	6.3	3.5	1.7	11.5
	AREA 6	6.5	9.9	1.9	18.2

Table 2 .

 2 -Percentage of the contaminated wines depending on the area studied versus the total wine

	sampling
		TCA TeCA PCA TCP TeCP TBA TBP % contaminated wines
	AREA 1 3.7	2.2	0.7	8.8	0	2.9	0	16.1
	AREA 2 4.5	1.8	2.7	1.8	0	0	0	9.8
	AREA 3	0	0	12.5 25.0	0	0	0	37.5
	AREA 4 5.7	6.9	1.1	4.0	0.6	2.3	0	11.45
	AREA 6 5.9	9.3	3.6	4.0	0.4	1.7	0	18.2
	Note: TCA (2,4,6-trichoroanisole); TeCA (2,3,4,6-tetrachloroanisole); PCA
	(pentachloroanisole); TCP (2,4,6-trichlorophenol); TeCP (2,3,4,6-tetrachlorophenol);
	TBA (2,4,6-tribromoanisole); TBP (2,4,6-tribromophenol).

Table 3 .

 3 -Percentage of cork taint wines according to the different aged wine categories and the compounds found.

	Compounds	Aged-6 Aged-12 Aged-24 TOTAL
	TCA	2.1	7.7	0.8	5.3
	TeCA	2.8	9.0	1.6	6.8
	PCA	0.9	4.1	0.8	2.8
	TCP	2.7	4.4	1.1	4.8
	TeCP	0.2	0.3	0.0	0.3
	TBA	0.6	1.9	1.1	1.8
	TBP	0.0	0.0	0.0	0.0
	TOTAL	6.9	19.9	4.1	16.1
	Note: TCA (2,4,6-trichoroanisole); TeCA (2,3,4,6-tetrachloroanisole);
	PCA (pentachloroanisole); TCP (2,4,6-trichlorophenol); TeCP
	(2,3,4,6-tetrachlorophenol); TBA (2,4,6-tribromoanisole); TBP (2,4,6-
	tribromophenol).

Table 4 .

 4 -Humidity data 2004/2005 of the different geographical production areas and the percentage of contaminated wines.

	Food Additives and Contaminants	Page 18 of 20
		Humidity
		(mm)	% contaminated wines
	AREA 1	444.6	16.1
	AREA 2	357.5	9.8
	AREA 3	450.0	37.5
	AREA 4	383.6	11.5
	AREA 6	505.2	18.2

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Table 5 .

 5 -Mean concentrations of the halophenols and haloanisoles detected in the 966 quality red wines.

		OT	Mean Concentration	Concentration Range
	Compounds	[ng L -1 ]	[ng L -1 ]	[ng L -1 ]
	TCA	5-10	76.5	546-2.6
	TeCA	14-25	68.4	775-2.2
	PCA	4000	64.9	454.3-2.3
	TCP	Unknown	115.3	521.22-4.55
	TeCP	Unknown	12.5	30.5-.3.4
	TBA	8	272.5	847.3-10.6
	TBP	Unknown	0.0	0
	Note: TCA (2,4,6-trichoroanisole); TeCA (2,3,4,6-tetrachloroanisole);	PCA
	(pentachloroanisole); TCP (2,4,6-trichlorophenol); TeCP (2,3,4,6-tetrachlorophenol); TBA
	(2,4,6-tribromoanisole); TBP (2,4,6-tribromophenol); OT (Olfactory Threshold)

Table 6 .

 6 -Red wine distribution according to the different geographical areas and relation with the contaminated wines studied.

	%

Red wine consumption % Contaminated wines Contaminates wines in the market AREA

				Page 20 of 20
	1	11.8	16.1	1.9
	AREA 2	9.4	9.8	0.9
	AREA 3	0.3	37.5	0.1
	AREA 4	24.4	11.5	2.8
	AREA 6	54.1	18.2	9.9

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Food Additives and Contaminants

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Page 8 of 20 http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.ukFood Additives and Contaminants


Natasha Sahgal

Rachel Needham

F Javier Cabañes

Naresh Magan
email: n.magan@cranfield.ac.uk

Prof N Magan

Potential for detection and discrimination between mycotoxigenic and non-3 toxigenic spoilage moulds using volatile production patterns -a review 4 5

Keywords: volatile fingerprints, electronic nose technology, mycotoxins, spoilage moulds, 18 early detection

Potential for detection and discrimination

mycotoxigenic moulds in the food production chain. The development of sensor arrays which 5 respond to the presence of different volatiles produced by such moulds have been examined 6 as a potential method for the development of such detection systems. Commercial devices 7 based on such sensor arrays, so called electronic noses have been examined extensively for 8 the potential application for determining the presence of mycotoxigenic moulds in food raw 9 materials. There is also interest in using the qualitative volatile production patterns to 10 discriminate between non-mycotoxigenic and mycotoxigenic strains of specific 11 mycotoxgenic species, e.g. Fusarium section Liseola, Penicillium verrucosum and 12 Aspergillus section Nigri. This paper reviews the technology and the available evidence that 13 the non-destructive analysis of the headspace of samples of food raw materials or the 14 discrimination between strains (mycotoxigenic and non-mycotoxigenic) can be determined 15 using volatile fingerprints. [START_REF] Legan | Mould spoilage of bread: the problem and some solutions[END_REF] 17

Introduction 1

Food raw materials are colonised by a wide range of mycotoxigenic moulds including 2

Aspergillus flavus (aflatoxins), Penicillium verrucosum (ochratoxins, citrinin), Aspergillus 3 ochraceus (ochratoxins), Fusarium section Liseola (fumonisins), and Aspergillus section 4

Nigri species (ochratoxins) [START_REF] Aldred | HACCP and mycotoxin control in the food chain[END_REF]). There has been particular interest in the 5 development of prevention strategies to minimise the exposure of consumers to mycotoxins 6 [START_REF] Aldred | HACCP and mycotoxin control in the food chain[END_REF]. This strategy requires the early and rapid detection of mycotoxigenic 7 moulds and their toxins. There is also significant interest in being able to discriminate 8 between strains of a species with regard to the ability to produce specific mycotoxins. 9

Volatiles can be used to detect early mould contamination of cereals. Studies by 10

Abramson et al. (1983) and [START_REF] Tuma | Odor volatiles associated with 16 microflora in damp ventilated and non-ventilated bin-stored bulk wheat[END_REF] suggested that in stored barley and wheat 3-11 octanone, 1-octanol, and 3-methyl-1-butanol were key volatiles. These studies depended on 12 the use of GC-MS to obtain the information. These volatile fingerprints also vary with 13 individual microorganisms. For example, using GC-MS it has been shown that the volatile 14 profiles produced by Pseudomonas fragi, Saccharomyces cerevisiae and Penicillium 15 verrucosum are very different [START_REF] Needham | Early detection and 8 differentiation of spoilage of bakery products[END_REF]. However, this requires significant 16 technical and analytical expertise. The development of sensor arrays, so called electronic nose 17 systems, which could simulate the odour detection in the human olfactory system were 18 developed to facilitate the detection of volatile fingerprints in headspaces of samples to enable 19 rapid detection systems to be developed for applications in a wide range of areas, including 20 food spoilage. It is well known that microbial contaminants produce a range of volatiles. 21 22 Sensor arrays for detection of volatile production patterns 23 Gardner and Bartlett (1994) defined sensor arrays used for detection of volatile fingerprints in 24 the following way: "an electronic nose is an instrument which comprises an array of 25 electronic chemical sensors with partial specificity and an appropriate pattern recognition 26 system, capable of recognising simple or complex odours". Table 1 summarises the 1 development of such sensor arrays from a historical perspective. Table 2 shows the range of 2 food matrices in which this technology has been examined. [START_REF] Jelen | Trichodiene as a volatile 4 marker for trichthecene biosynthesis[END_REF] The system consists of three basic building blocks: the vapour phase flows over a 4 sensor array, the interaction with the sensor surfaces occurs, and this response is analysed 5 using software for an output and interpretation. There are a number of different types of 6 sensor arrays which are used. Sensor technology has developed rapidly over the past decade 7 and this has resulted in a range of different sensor formats and the development of complex 8 microarray sensor devices. In the specific area of electronic nose systems, several different 9 physicochemical techniques have been used to produce sensor arrays for odour 10 characterisation. The type of sensor arrays used include: conducting polymers, metal oxides, 11 metal oxide silicon field effect sensors, piezoelectric crystals, surface acoustic wave devices, 12 optical sensors and electrochemical sensors [START_REF] Turner | Electronic noses and disease diagnostics[END_REF]. 13 14 Detection of mould spoilage in food raw materials [START_REF] Tuma | Odor volatiles associated with 16 microflora in damp ventilated and non-ventilated bin-stored bulk wheat[END_REF] It has been shown that raw materials such as grain which is poorly stored have off-odours due 16 to alcohols, esters, ketones and mono and sesquiterpenes and aldehydes. The dominant 17 volatiles in grain were found to be 3-methyl-1-butanol, 1-octen-3-ol and 3-octanone ( Magan 18 & Evans, 2000). Studies with grain having different levels of moulding and natural samples 19 showed that by using a standardised grain amount and a conducting polymer array of sensors 20 and a radial based-neural network it was possible to carry out real time analyses of grain 21 samples in 10 mins [START_REF] Evans | Evaluation of 18 a radial basis function neural network for determination of wheat quality from 19 electronic nose data[END_REF]. This enabled a decision to be made on whether grain 22 was acceptable or not. Interestingly, results were very comparable with those produced by an 23 odour panel classification. This approach was based on acceptable or unacceptable and 24 showed a small group of samples in a so-called zone of uncertainty which suggested that they 25 were in the process of going mouldy and thus needed further investigation. 26 Other studies using metal oxide sensors have suggested that the presence of 1% 1 contaminated grain could be discriminated [START_REF] Costello B P J D L, Ewen R J, Gunson | A prototype sensor system for the early detection of microbially linked 16 spoilage in stored wheat grain[END_REF]. However, in trials with 2 harvested naturally contaminated grain some false positives were obtained when compared to 3 other criteria used at intake facilities for processing. The results were, importantly, not found 4 to be linked to grain moisture content. These studies all suggest that quality of grain can be 5 effectively managed using this approach. Similar studies by [START_REF] Börjesson | Electronic nose for odor 9 classification of grains[END_REF], Jonsson 6 et al. (1997) and [START_REF] Olsson | Detection and quantification of 11 ochratoxin A and deoxynivalenol in barley grains by GC-MS and electronic nose[END_REF] showed that there was some value in quality grading of 7 cereals using the electronic nose approach. 8

Research has also been carried out using a mass spectrometry-based e-nose system to 9 examine mould contamination of Spanish bakery products. By using a range of data analysis 10 techniques including PCA, DFA and fuzzy ARTMAP and solid phase micro-extraction to 11 concentrate the volatiles produced by spoilage moulds successful (98%) discrimination of 12 mould growth from controls was possible within 48 hrs (Vinaixa et al., 2004). This was 13 possible prior to any visible growth being observed. After 96 hrs, 88% discrimination 14 between a range of spoilage species was achieved. Further studies on spoilage fungi in bakery 15 products using this same approach has recently been reported by [START_REF] Marin | Use of an MS-electronic nose for prediction of early fungal spoilage of bakery 25[END_REF]. [START_REF] Legan | Mould spoilage of bread: the problem and some solutions[END_REF] employed the MS-electronic nose to detect Eurotium, Penicillium and Aspergillus species in 17 Spanish cake products. They found that volatile production patterns were positively correlated 18 with ergosterol as a biomass marker of fungi after 2, 4 and 7 days. This measurement 19 approach using a relatively sophisticated e-nose system required 20-25 mins per sample. This 20 also has potential to be included in a QA system for processing of raw materials. in submerged culture and found that A. flavus produced distinct compounds such as α-2 gurjunene, trans-carophyllene and cadinene which were only present in aflatoxigenic strains . 3 There was some correlation between production of these compounds and aflatoxin synthesis. 4

These studies used standard analytical techniques such as GC and GC-MS. [START_REF] Jelen | Production of volatile 23 sesquiterpenes by Fusarium sambucinum strains with different abilities to synthesize 24 trichothecenes[END_REF]Jelen et al. ( , 5 1997a[START_REF] Jelen | Volatile fungal metabolites and their relation to the spoilage of 6 agricultural commodities[END_REF]) also attempted to find potential marker volatiles for trichothecene production by 6

Fusarium sambucinum and suggested that different sesquiterpenes were produced by 7 toxigenic and non-toxigenic strains. More recently, Jelen & Grabarkiewicz-Szczesna (2005) 8 examined a range of Aspergillus ochraceus and other Aspergillus species and tried to relate 9 volatile production patterns using GC-MS and ochratoxin production. They found that, 10 regardless of toxin production capacity, similar key volatiles such as 1-octen-3-ol, 3-octanone, 11 3-octanol, 3-methyl-1-butanol, 1-octene, and limonene were produced. The predominant 12 volatile was 1-octen-3-ol and was produced by all strains. While environmental conditions of 13 temperature and water content optima for quantified volatiles and ochratoxin production were 14 different, the volatiles did not facilitate discrimination of A. ochraceus strains. In studies of 15 barley grain [START_REF] Börjesson | Volatile metabolites and other indicators of 6 Penicillium aurantiogriseum growth on different substrates[END_REF] found that the highest production of volatile fungal 16 metabolites precedes ochratoxin production. 17

Quantitative studies of volatile organic compounds with a trichothecene-producing 18 strain of Fusarium sporotrichioides, and ochratoxigenic and non-ochratoxigenic strains of P. 19 verrucosum suggested that volatile terpenes were linked to the formation of trichothecenes by 20 Fusarium spp. and probably accelerated production of volatile ketones by the ochratoxigenic 21 strain of P. verrucosum [START_REF] Pasanen | Volatile organic metabolites associated with 14 some toxic fungi and their mycotoxins[END_REF]. Jelen et al. (1997b) found that trichodiene, an 22 intermediate of trichothecene production was elevated in harvested grain spikes colonised by 23 Fusarium head blight species when harvested and incubated. They suggested that this could 24 be a good marker for differentiation between infection by toxigenic and non-toxigenic strains. 25

Use of electronic nose systems for discriminating mycotoxigenic species and strains 2

The question arises as to whether the use of qualitative volatile fingerprints which can be 3 detected by using e-nose systems can be used for the rapid early discrimination of toxin and 4 non-toxin producers. Studies by [START_REF] Keshri | Detection and differentiation between mycotoxigenic and non-14 mycotoxigenic strains of two Fusarium spp. using volatile production profiles and 15 hydrolytic enzymes[END_REF] used a conducting polymer based e-5 nose system (BH114, Scensive Technologies, Leeds, U.K.) to try and use the volatile 6 production patterns to try and differentiate between strains of F. verticillioides and also F. 7

proliferatum able to produce fumonisins and strains that did not produce any. They grew up 8 these fungi on cereal-based substrates for 48-96 hrs and examined the volatile production 9 patterns using PCA and Cluster analyses. This showed that it was possible to differentiate 10 between the control blanks, the non-toxigenic and three toxigenic strains of each of these 11 species (Figure 1). Interestingly, parallel studies carried out on hydrolytic enzyme activity, 12 showed that both total and specific enzyme activity changes indicative of growth occurred 13 only after 96 hrs, much later than that detected with the e-nose (48-72 hrs). 14 Subsequently extensive studies were conducted with both toxigenic and non-toxigenic 15 strains of A. flavus (three of each; aflatoxins) and P. verrucosum (two to three of each; 16 ochratoxin, citrinin, both or none; [START_REF] Needham | Use of electronic nose technology for the early detection of spoilage in 3 bakery products[END_REF]. Strains of A. flavus were supplied by Dr. 17

A. Neschi, Rio Cuarto University, Argentina and P. verrucosum strains were provided by the 18 Dr. P.V. Nielsen, BioCentrum-DTU, Lyngby, Denmark. Studies for A. flavus were conducted 19 on milled maize-based media and those with P. verrucosum on 2% wheat agar and on bread 20 analogues for comparison at 0.95 water activity. The substrates were inoculated with 100 µl 21 of 10 6 CFU ml -1 of relevant strains and then incubated for 24, 48 and 72 hrs. The methods for 22 analyses of headspace were as described previously by [START_REF] Keshri | Detection and differentiation between mycotoxigenic and non-14 mycotoxigenic strains of two Fusarium spp. using volatile production profiles and 15 hydrolytic enzymes[END_REF]. Figure 2 23

shows an example of the dendrogram for A. flavus strains examined at the 95% confidence 24 limits. This showed that there was no clear clustering of strains based on their ability to 25 produce aflatoxins. This suggested that it was difficult to separate strains of this species 1 effectively. 2

Figure 3 shows the PCA plot obtained for the different strains when incubated for 72 3 hrs. This shows that PC1 and PC2 accounted for 92% of the variance and showed 4 discrimination between some of the strains. An examination of the Cluster analyses of the 5 data on bread analogues showed that it was possible to separate out the ochratoxin and 6 ochratoxin + citrinin producers (Figure 4). However, there was less discrimination between a 7 citrinin only producer and that which produced none. 8

Recently we have also examined the potential of using alternative sensor formats to 9 evaluate the potential of using volatile production patterns for discrimination between 10 members of the A. niger Section Nigri species. Up to now, the taxonomy of black aspergilli is 11 not very clear because it is primarily based on morphological criteria and in some cases (e.g. 12 A. niger aggregate) the differences between species are very subtle [START_REF] Abarca | Taxonomy and significance of black 24 Aspergilli[END_REF]. 13 There is already good information on the molecular differentiation between these strains 14 detailed in Table 3 [START_REF] Abarca | Taxonomy and significance of black 24 Aspergilli[END_REF]. We have examined the volatile production patterns 15 on different nutrient media. In this case we found that grape juice-based media were best for 16 optimising volatile production. These studies showed that it was possible to differentiate 17 between species based on the volatile production patterns detected with metal oxide sensor 18 array using an AlphaMoss 3000 machine. A similar protocol was followed as used by 19 [START_REF] Needham | Early detection and 8 differentiation of spoilage of bakery products[END_REF] except that agar discs (1 cm diam) were placed in 10 ml glass vials and 20 crimp sealed before randomising and placing in the autosampler. In all cases at least 5 21 replicates were used per treatment. Figure 5 shows the discrimination achieved between the 22 species examined and this accounted for 96% of the data in PC1 and PC2. The Cluster 23 analyses based on the Euclidian distances showed some discrimination between the species of 24 the A. niger section Nigri used is shown in Figure 6. Subsequent studies on cracked maize 25 with different ochratoxin producing species such as P. verrucosum, A. ochraceus and A. 26 This review of recent work carried out on application of e-nose technology for the rapid early 6 diagnosis of mycotoxigenic spoilage moulds suggests that there is some promise in this 7 approach as part of a "prevention strategy". Previous studies have shown that potential exists 8 for using sensor arrays to differentiate between toxigenic and non-toxigenic strains of 9 Fusarium section Liseola, Penicillium verrucosum and Aspergillus section Nigri species. For 10 example, [START_REF] Keshri | Detection and differentiation between mycotoxigenic and non-14 mycotoxigenic strains of two Fusarium spp. using volatile production profiles and 15 hydrolytic enzymes[END_REF] carried out in vitro studies on grain-based media using 11 strains of Fusarium verticillioides and Fusarium proliferatum. Using the same e-nose system, 12 based on a 14 conducting polymers sensor array, they were able to discriminate between 13 uninoculated controls, a non-toxigenic strain and 3 mycotoxin producing strains of both 14 organisms after 48-72 hrs with PCA and Discriminant function analyses. This was much 15 earlier than hydrolytic enzyme production of β-D-glucosidase, α-D-galactosidase and N-16 acetyl-β-D-glucosaminidase. These were only demonstrated to significantly increase after 72 17 hrs incubation. [START_REF] Olsson | Detection and quantification of 11 ochratoxin A and deoxynivalenol in barley grains by GC-MS and electronic nose[END_REF] used an e-nose to detect ochratoxin A in barley grains 18 and to also predict if the level of the toxin was below the legislative limit of 5 µg kg -1 . 19

Studies by [START_REF] Needham | Detection and differentiation of microbial spoilage organisms 5 of bakery products in vitro and in situ[END_REF] showed that it was not possible to discriminate a 20 citrinin producing strain of P. verrucosum in situ although this was possible in vitro on 21 unmodified 2% wheat agar. This discrimination was concentration dependent and when using 22 a much lower initial spore concentration a reduced number of strains was observed which 23 could be effectively discriminated, based on ability to produce ochratoxin or citrinin. 24 However, in bakery products such as bread sometimes, even if the mycotoxigenic strain is 25 [START_REF] Legan | Mould spoilage of bread: the problem and some solutions[END_REF], which may account for 1 the difficulty in sometimes being able to discriminate between such strains. However, the 2 ability to detect spoilage fungi and mycotoxins prior to visible moulding is a key criteria and 3 in some cases this is achievable using qualitative volatile production patterns. Also analysis 4 and differentiation is prior to visible growth being observed. This is important as an approach 5 which could give an early indication of potential for mycotoxin contamination in raw 6 commodities. This may have particular applications as a tool for discriminating between 7 strains as an additional measurement to morphological and molecular approaches as well as in 8 quality assurance systems. Potential also exists for application in the animal feed chain where 9 particular mycotoxins, e.g. zearalenone, some trichothecenes and aflatoxins are particularly 10 important contaminants. 11

The rapid development of sensor technologies and miniaturisation of sensor arrays 12 suggests that the sensitivity and robustness have been improving significantly. This will 13 provide opportunities for more sensitive hand held devices to be used and the data analyses to 14 be carried out remotely by using Neural Networks and other bioinformatics approaches. We 15 are also now examining the potential for correlating the qualitative fingerprints with SIFT-MS 16 (selective ion flow tube mass spectrometry), to monitor trace gases in real time without 17 sample pre-treatment and can cope with a wide dynamic range, e.g. percentage concentrations 18 in water or a few ppb of a trace compound in the same sample analyses to identify the key 19 volatile compounds responsible for the discrimination achieved [START_REF] Turner | A longitudinal study of ammonia, acetone and propanol 21 in the exhaled breath of 30 subjects using selected ion flow tube mass spectrometry, 22 SIFT-MS[END_REF]. 20

21 22Use of volatiles to detect mycotoxigenic spoilage moulds 23 Fungi

 2123 producing secondary metabolites are known to use different biosynthetic pathways, 24 depending on the final product. For example, production of aflatoxins by A. flavus group 25 follows a general scheme of acetate polyketide anthraquinones et al. (1993) studied aflatoxigenic and non-aflatoxigenic A. flavus strains 1

2 ( 3 4

 23 suggests that it is possible to use headspace analyses of qualitative volatiles to 1 differentiate between contamination with these different mycotoxigenic spoilage fungi[START_REF] Cabañes | Identification of black Aspergilli species 11 responsible for ochratoxin A contamination of food using qualitative volatile 12 fingerprints[END_REF].Discussion and conclusions 5

  surface, no mycotoxins are produced

  A brief historical perspective on development of sensor array systems for odour 1 detection and development of electronic nose type approaches 2 3 1962: Stereo-chemical theories of olfaction 4 1978: Structure-activity relationships in human chemoreception 5 1982: First development of a model nose using three sensors with broad 6 sensitivity (Persaud & Dodd) 71988: Term 'electronic nose' used for 1 st time 8 1990s: First commercial devices developed using conducting polymer sensor arrays 9 1990s: Applications in food, environment, medicine using generic research-based devices 10 >2000 onwards: More targeted approaches of e.nose systems for specific use in food,

Figure 1 . 8 Figure 2 . 13 Figure 3 . 18 19Figure 4 .Figure 5 . 5 Figure 6 .Figure 1 .

 1821331845561 Figure legends3

Figure 2 .Figure 3 .FoodFigure 4 .Figure 5 .

 2345 Figure 2. Sahgal et al.

Figure 6 .

 6 Figure 6. Sahgal et al.

Table 2 .

 2 Summary of the range of food matrices and types of spoilage which have been

	3
	4	examined using e.nose systems
	5
	6	Food product	Types of spoilage
	7	Grain/flour	Moulds/insects/toxin
	8	Bread	bacteria/yeasts/moulds
	9	Milk	bacteria/yeasts
	10	Cheese	moulds
	11	Coffee	bacteria/yeasts/moulds
	12	Fish	microbial taints/freshness
	13	Tea	cultivars/speciality coffees
	14	Beers	tainting
	15	Wines	tainting/yeasts
	16	Nuts	quality/toxins
	17	Fruit	quality/disease
	18	Meat	microbial taints/freshness
	19
	20
	21

Table 3 .

 3 Strains of A.niger section Nigri used in this study which have been discriminated 3

	4	previously using molecular methods (Abarca et al., 2004). Key: N, two fragments 519 and 76
	5	bp; and T, one fragment of 595 bp.
	6
	7	Reference No.	Species	Source	Geographic OTA	RFLP
	8				Origin	Production	pattern
	9	A-941	A.carbonarius	grapes	Spain	+
	10	A-75	A.niger aggregate	feedstuff	Spain	+	N
	11	A-946	A.niger aggregate	coffee	Portugal	-	N
	12	A-947	A.niger aggregate	grapes	Spain	-	T
	13

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