Christoph Von Holst

Ana Boix

Vincent Baeten

Jeroen Vancutsem

Gilbert Berben

Baeten

Keywords: Animal feed, Bovine spongiform encephalopathy, Processed animal proteins (PAPs), Meat-and-bone-meal (MBM), Species identification, Microscopy, Immunoassays

Table 1. The ban on Processed Animal Proteins (PAPs) in animal nutrition and the corresponding European regulation. For instance, EC Regulation 999/2001 prohibits the use of PAPs from ruminants and pigs in the feed for ruminants. Regulations written in bold have permanent character. The ban on PAPs according to Regulations written in italic may be lifted provided that animal specific tests are available. For instance, pigs could be fed on PAPs from poultry if analytical methods allow for specific detection of porcine PAPs in the presence of PAPs from poultry. Nevertheless, there are still claims that major and minor deviations from the improved protocol would gain comparable result. This applies especially to the two-solvent Method (also called the "French Method"), which uses two instead of one solvent in the sedimentation part of the protocol [START_REF] Michard | Note concernant le protocole de détection des farines de viande, d'os et de poisson dans les aliments pour animaux[END_REF] Though microscopy is the only official method for the detection of PAPs in feed, an inherent limitation of this method is the lack of animal (e.g. ruminants) or even species specificity. For instance, the results from a former study revealed [START_REF] Gizzi | Determination of processed animal proteins, including meat and bone meal, in animal feed[END_REF]) that the detection of mammalian PAPs in the presence of poultry meal is too demanding for the majority of European control laboratories. In the same study laboratories applied other methods such as PCR or immunoassays on the same samples because these approaches were expected to be more suitable for species detection in PAPs. However, the study showed that most of the various PCR methods also experienced problems in detecting mammalian and ruminant PAPs, whereas some of the immunoassays reported promising results. In fact, some of the immunoassays were able to detect ruminant PAPs at a concentration level of 0.5 %, but failed when the samples contained 0.1 % of ruminant PAPs. It was therefore considered as important to know more about the current capability of immunoassays of determining the species in PAPs present in feed and to establish whether the sensitivity of the methods has been improved. Four laboratories which participated in the former study [START_REF] Gizzi | Determination of processed animal proteins, including meat and bone meal, in animal feed[END_REF]) where asked to participate in a second study analysing 50 samples containing PAPs of cattle and pork separately. This study was designed as pre-validation in order to establish the most promising tests which merit further investigation by conducting a full validation study.

- 0.1 0.1 0.1 - - - - - - 0.5 - Bovine MBM 133°C (%) - - - - - - 0.1 - - - - - Bovine PAP 129°C (%) - - - - - - - 0.1 - - - - Porcine MBM (%) - - - - - - - - 5 - - - Fishmeal (%) - - - 5 - 5 - - - - - - Feather meal (%) - - 5 - 0.5 - - - - - 5 5 DCP (%) - - - - - - - - - 2 -
In particular it was of interest to know whether these tests allow for the detection of PAPs at different taxonomic levels such as PAPs from mammals and ruminants at 0.1 %. It was also important to establish the selectivity of the immunoassays. For instance, a test for ruminant PAPs should give a negative result when the feed samples only contain porcine material.

Experimental

Organisation of the study

For the intercomparison study each participant received:

(1) A protocol of the study containing the required information for the participants of the exercise.

(2) Laboratories applying microscopic analysis:

A set of 24 coded feed samples consisting of 8 different materials each in blind triplicate as shown in Table 2.

Laboratories applying immunoassays analysis:

A set of 50 coded feed samples consisting of 7 different materials in various numbers of replicates as shown in Table 2.

(3) A report template in Excel format in which the participants had to fill the results of their analysis for each parameter. In addition the laboratories were also requested to provide the organiser of the study with information about the method applied using an electronic form.

[Insert Table 2 about here] Since there is no legal limit for PAPs in feed, the laboratories were requested to express their results in terms of "present", "not present" or "no results" without indicating the concentration of the MBM in the samples. The latter response corresponded to inconsistent results or was indicated by laboratories when the method did not allow determining a specific parameter (e.g. the detection of porcine PAPs by a

Statistics calculated

Important method characteristics of the microscopic methods were calculated according to Langton et al. 2002, which Presence of fishmeal at a realistic level of 5 % that could interfere with the detection of constituents from terrestrial animals when using microscopy and immunoassays.

Presence of feather meal that could interfere with the detection of constituents (at 0.1 % and 0.5 % respectively) from mammalian animals when using microscopy.

Presence of meat and bone meal from pig by-products could interfere with the detection of constituents from ruminants when using immunoassay techniques.

Presence of dicalcium phosphate from organic origin could interfere with the detection of constituents from mammals and ruminants when using immunoassay techniques.

The base of the test material (MAT I) was a compound feed for bovine containing Different processed animal proteins were included in the study. The mammalian MBM used in the study was a mix of bovine and porcine processed material with a bone content (of) about 15.31 % (SD = 1.24) and is described elsewhere [START_REF] Gizzi | Determination of processed animal proteins, including meat and bone meal, in animal feed[END_REF]).

The MBM feed ingredients were analysed by PCR in order to check the species present in the sample, confirming that these samples mainly contained bovine and porcine materials with low amounts of poultry material. The content of bovine MBM was about 45 %. The pure cattle and pig MBMs representing a typical mixture of different proteins as present in carcasses and the feather meal were obtained from a pilot plant using pure animal by-products of each species. The meals were treated at temperature 133°C and 3 bar for 20 minutes. Afterwards the material was dried under atmospheric conditions until the moisture content was below 10%. Finally the product was pressed and ground.

Applying PCR confirmed that the cattle, pig and feather materials contained exclusively PAPs from the indicated species. The PAPs of MAT VIII were pure cattle meat that was treated at temperature at 129°C for 20 min. The meat was processed in a laboratory autoclave applying a procedure that mimics the sterilisation conditions in an industrial batch type rendering system quite well as described elsewhere [START_REF] Pallaroni | Determination of rendering plant sterilisation conditions using a commercially available ELISA test kit developed for detection of cooked beef[END_REF]).

The process, in short, consists of mincing the meat and adding water to form a slurry. The material and a temperature probe were transferred in a plastic bag and placed in the autoclave ensuring that the bag was completely surrounded by water. After completion of the process the material was dried in an oven over-night at 70°C and finally ground in a centrifugal mill. The indicated temperature refers to the value measured by the temperature probe.

The fishmeal was obtained directly from a fishmeal producer and its proportion of bones was about 12.99 % (SD = 0.04). The feather meal was obtained from a pilot plant and produced from poultry by-products and its proportion of bones was about 0.06 % (SD = 0.03). The material was treated at 133°C and 3 bars for 20 min. Afterwards the material was dried under atmospheric conditions until the moisture content was below 10%. Finally the product was pressed and ground. The fishmeal and the feather meal were analysed by PCR confirming that the fishmeal did not contain bovine, porcine and poultry materials and that the feather meal did not contain bovine and porcine materials.

The different MBMs, which were mammalian MBM (MMBM), cattle meal, pig meal, poultry meal and fishmeal, DCP and the compound feed were used as raw product without grinding to a fine powder prior to the mixing procedure. This was required since grinding the sample is part of the microscopic analysis. Preparing the samples using the raw material is very demanding, especially when considering the low target concentration of 0.1 % MBM in some of the test materials. In order to have an acceptable homogeneity for the fortified samples (MAT II-XII) the stepwise dilution procedure as described in a former study [START_REF] Gizzi | Determination of processed animal proteins, including meat and bone meal, in animal feed[END_REF]) was utilized. The amount of Sufficient homogeneity of each material was established by analysing five to ten randomly selected bags using the near-infrared microscopic method (NIRM) and a PCR method that proved to be suitable for the purpose of this analysis [START_REF] Gizzi | An overview of tests for animal tissues in feeds applied in response to public health concerns regarding bovine spongiform encephalopathy[END_REF].

NIRM is based on the analysis of several hundreds of particles of the sediment fraction using a near-infrared spectrometer coupled to an adapted microscope. Details of the method are given elsewhere [START_REF] Baeten | Detection of banned meat and bone meal in feedstuffs by near-infrared microscopy analysis of the dense sediment fraction[END_REF]). In particular it was important to demonstrate that each of the sample bags of the test materials containing 0.1% MBM (i.e. MAT II, MAT III, MAT IV, MAT VII in Table 2) contained enough bones for microscopy. The test material was regarded as fit for purpose when the analysis of all test materials containing MBM at this level would gain a positive result of this method.

The analyses of the test material confirmed that in all test items investigated the MBM specific fraction of the sediment was sufficiently constant.

The homogeneity of the test materials MAT IV, MAT VII and MAT VIII were also analysed by PCR. The results are expressed as the Mean Ct value (threshold cycle) and the standard deviation calculated on the three or four replicates per bag as well as for the mean values of the five bags analysed (Table 2). All the samples were detected as positive regarding the presence of bovine DNA.

Information on the microscopic methods applied

In microscopic analysis the samples are ground by various means and subjected to the sedimentation procedure by treating the samples with a halogenated solvent. Bones According to the official European method only tetrachloroethylene (density 1.62 g/ml) is used. Therefore all particles such as bones and minerals with a higher density form the sediment. In contrast, the two-solvent Method utilised two solvents for the sedimentation, which are tetrachloroethylene (density 1.62 g/ml) and a mixture (density 2.4 g/ml) of tetrachloroethylene and tetrabromoethane (42/58, v/v). All particles with a density between 1.62 and 2.4 g/ml including bones concentrate in the layer between the two organic solvents (sediment fraction I), whereas minerals with a higher density than 2.4 g/ml concentrate at the bottom of the two solvents (sediment fraction II). Therefore sediment fraction I contains less interfering particles thereby facilitating the identification of animal specific constituents. Careful handling of the sedimentation is required to avoid mixing of both organic solvents.

For the sedimentation process the following glassware is applied. As described in the European official method (Commission Directive EC/2003/126) two types of sedimentation glassware can be used: a conical bottomed settling beaker (Figure 1) or a separation funnel.

[Insert Figure 1 about here] Two types of beakers can be used: an open beaker without cock and an open beaker with cock. In the beaker without cock, the sedimentation solvent is poured out carefully while the sediment remains on the bottom. In the beaker with cock, the sediment is caught in a small tray that is closed by turning the cock. Since the two-solvent Method uses two organic solvents for the sedimentation, this method requires a flexible tube to [Insert Figure 2 about here] Important aspects of the two methods investigated in this study are summarised in Table 3. When comparing the two protocols it is clear that the use of two different organic solvents of the two-solvent Method renders the execution of the method more complicated compared to the European official method in which only one solvent used.

[Insert Table 3 about here] Information on the immunoassays included in the study.

Four methods (A, B, C and D) developed by three institutes were included in the study.

As shown in Table 4 the immunoassays differed considerably in terms of the target animal, the target tissue and the design of the test. Method A and B were lateral flow immunochromatographic assays and from the same institute but had different sample preparation procedures thereby achieving a different sensitivity. Both tests had ruminant proteins as target. The design of method C was a classical ELISA and allowed the detection of proteins from various animals including ruminants. Method D was developed as dip stick immunoassay that is suitable for the detection of PAPs from all animals without any distinction between species. In addition, the tests measured PAPs exclusively from mammalians.

[Insert Table 4 about here]

Results and discussion

Intercomparison study of microscopic methods

In this discussion the participating laboratories are subdivided into two groups based on -Evaluation of the two-solvent Method as described in [START_REF] Michard | Note concernant le protocole de détection des farines de viande, d'os et de poisson dans les aliments pour animaux[END_REF] The content of the samples has been reported at three systematic levels: presence of total PAPs, presence of PAPs with distinction between constituents originated from terrestrial animals and fish and a further distinction to mammalian or avian origin. A first target parameter was whether laboratories are able to detect the presence of PAPs from all terrestrial animals (mammals and poultry) and fish as shown in Figure 3. For this overview the results from all materials that contained PAPs were pooled, i.e. all materials with the exception of MAT I which was the blank material. Most of the samples were correctly classified. Sixteen samples out of 336 were wrongly classified as negative (SE = 95%). Seven of these sixteen negative deviations have been found to be contradictory results (e.g. positive for fishmeal but negative for total PAPs) produced by two laboratories including five results by one laboratory due to an error against the definition of PAPs and two results by another laboratory due to a lack for a final check for plausibility. Seven other negative reported results were from MAT V (feather meal 0.5%), the matrix with the lowest amount of bones of all the samples with animal material with SE = 83%.

Evaluation of the official

[Insert Figure 3 about here] For the discussion of the next level (PAPs from terrestrial animals) the results from all samples that contained terrestrial PAPs (MBM or feathermeal) were pooled, obtaining 90 % of correct positive results. Focusing on the results from MAT IV that contained 0.1 % of MBM and 5 % of fishmeal revealed that due to the presence of fishmeal the sensitivity decreased from 90 % to 70 % confirming that large amounts of fishmeal can make the detection of terrestrial PAPs more difficult. In Table 5 the results of this study were compared with the results from other studies. The sensitivity of the method according to the new Directive EC/2003/126 (this study and the Stratfeed validation study) for MAT IV (0.1% MMBM in feed in the presence of 5% fishmeal) was 70 % and 77 %, respectively. Both studies, therefore, obtained comparable results but the sensitivity was higher compared to the two-solvent Method and the former Directive EC/98/88 (DG SANCO study 2003), confirming the superiority of the current European method. The results of these studies were comparable since the trial conditions such as the characteristics of the test material were almost identical. In another study (van Raamsdonk & van der Voet, 2003) that also complies with the new European method even higher values for the sensitivity were obtained (98%). However these results were not completely comparable with the results from the other studies due to a different design of the exercise, namely the bone fraction of the ruminant MBM used in the study (van Raamsdonk & van der Voet, 2003) was 54% and therefore higher than in the other [Insert Table 5 about here] The correct identification of the negative samples for the parameter terrestrial PAPs was calculated evaluating the pooled results from MAT I and MAT VI (Table 2), obtaining 90 % for the specificity. This value was higher compared to the specificity for the parameter total PAPs which was 77 % and calculated from the correct negative results of MAT I. This means that in the latter case more particles were erroneously identified as positive for the parameter total PAPs than in the case when exclusively looking for terrestrial PAPs. This result reflects the fact that the criteria for the identification of terrestrial PAPs are more strict compared to the identification of PAPs irrespective of the species. However, this corresponds to a lower sensitivity of the positive samples for total PAPs compared to terrestrial PAPs as shown in Figure 3.

Mammalian material was identified with a sensitivity of 68% (MAT II, III, IV, XI) with a high number of no results (77 of 192 samples). In the absence of feather meal or fishmeal (MAT II), mammalian material was detected with a sensitivity of 93%. The sensitivity for mammalian material drops from 80% in MAT XI (0.5% MMBM in 5% feather meal) to 62% in MAT III (0.1% MMBM in 5% feather meal) confirming that the mammalian material is more readily identified in higher concentrations. The sensitivity for mammalian material in the presence of fishmeal was only 38%, but the already low sensitivity for terrestrial animal material, which is the previous level, has to be taken in account. These results also demonstrated that the identification of mammalian PAPs, especially in the presence of PAPs from poultry is not feasible under Evaluation of the two-solvent Method. Five laboratories sent in their results. No contradictory results have been reported. Based on the protocol the laboratories applied, no labs were excluded. The laboratories were able to detect the presence of total PAPs with a sensitivity of 96% (Figure 4). This result is comparable with the sensitivity of the laboratories applying the directive EC/2003/126. With two false positive results for the blank sample, the specificity for the detection of total PAPs is 86%, which is higher than the specificity for laboratories applying the official method.

[Insert Figure 4 about here] On the next level (PAPs from terrestrial animals) 88% of the samples are correctly classified. For MAT IV (MMBM 0.1% + fish meal 5%), the sensitivity is 60% which is lower than the sensitivity calculated for the laboratories using the directive as already mentioned above. A possible explanation can be that bones are overlooked because of the higher concentration of the sediment which contains predominantly fishmeal and a possible partially sedimentation of the bone material into sediment fraction II. The fact that the execution of the two-solvent Method is more complicated compared to the official method could have contributed to lower sensitivity of the two-solvent Method.

Pre-validation study for the detection of PAPs in feed by immunoassays

Three laboratories reported results of analysis of the samples. Since one laboratory applied two different analytical approaches, results from four different methods were 4) indicate that methods A, B and C measured ruminant, whereas method D had two targets which were PAPs from all animals and mammalian PAPs. All immunoassay were evaluated only according to the claimed targets but not on results from parameters that were deduced from the target PAPs. For instance, the detection of ruminant PAPs also indicates the presence of mammalian animals but a negative result on ruminant PAPs does not necessarily demonstrate that there are no mammalian PAPs in the sample. This is due to the fact that mammalian PAPs include materials from animals that are not covered by this parameter. Therefore, the methods A, B and C were evaluated for the ruminant PAPs and method D for mammalian PAPs.

Immunoassay tests for the detection of ruminant PAPs. Method C was able to detect all samples from the ruminant MBM (MAT VII), whereas failed on the processed muscle proteins (MAT VIII), since all results were false negative. This was a surprising result given the lower heat treatment of the processed muscle proteins compared to the ruminant MBM samples. On the other hand, the protein profile of the ruminant MBM fit better to the targets of method C than the pure processed muscle proteins, since this method was raised against proteins from different tissues.

All methods failed when analysing the test samples from MAT IV that contained mammalian MBM at 0.1 %. However, since this MBM contained only 50 % ruminant PAPs, the true concentration of ruminant MBM in feed was 0.05 % and therefore below the target level of 0.1 %. The results of the samples that did not contain ruminant PAPs are shown in Figure 6. The applicability of the tests requires that unspecific proteins in blank feed and proteins from animals other than ruminants do not interfere with the detection of ruminant PAPs. In particular, false positive results should be avoided. The outcome of the analyses revealed that the methods A and C did not report any false positive result, whereas method B reported as positive for the presence of ruminant PAPs one out of 6 of the samples containing 5 % fishmeal and 1 out of 10 samples containing 5 % porcine. Interestingly, the method showing the highest sensitivity on the samples containing ruminant PAPs also reported two positive samples on samples that did not contain ruminant PAPs. However, the overall specificity of method B was still quite promising when pooling the results from all samples without ruminant PAPs, since 20 out 22 samples were correctly classified as negative.

[Insert Figure 6 about here] Regarding the analyses of the samples containing DCP, all results from method A and C were negative, whereas one sample out six from method B were positive. These results coincide with the results from the other materials, since method B turned out to be again as the most sensitive method. In addition the results indicate that DCP can be used in animal nutrition since the probability of "false positive results" is considered as low.

Immunoassay test for the detection of mammalian PAPs. The results of method D that was the only method in this study analysing for the presence of mammalian PAPs are shown in Table 6. The outcome of the experiments hinted at an insufficient sensitivity of this test, since only 6 out of 22 results were correctly classified as positive when pooling the results from MAT IV (MMBM 0.1%, 133 ºC + fishmeal, 5%), MAT VII (Bovine MBM 0.1%, 133 ºC) and MAT VIII (Bovine PAPs 0.1%, 129 ºC). All 10 samples from MAT IX (Porcine PAPs 5%, 133 ºC) were correctly classified as positive.

However, the concentration of porcine PAPs was 5 % and was therefore not a challenging task of the immunoassay.

[Insert

Conclusions

Comparing the results from the two microscopic based methods for total PAPs and PAPs from terrestrial animals the results of both methods are comparable with respectively 95% and 90% of the results correctly classified for the laboratories applying the Directive and respectively 96% and 88% for laboratories applying the twosolvent Method.

The performance of both methods in the presence of fishmeal is reduced, but still higher than the results obtained in the DG SANCO 2003 study since the rate of correct positive results is 60% for the two-solvent Method compared to 70% of the official European Method.

The detection of mammalian MBM by means of microscopy is very difficult. A high number of "no results" is reported due to the fact that laboratories cannot classify the detected bones (mammalian or poultry). Only in the case when no other animal material than MMBM is present in feed, identification is possible. None of the laboratories applying the two-solvent Method reports a result for mammalian MMBM. Similarly, method C showed an interesting performance profile due to its sensitivity towards various targets including ruminant PAPs. In contrast, method A did not show enough sensitivity for this target, since it failed on several samples that contained 0.1 % ruminant PAPs. Results of method D demonstrated that this test is not sensitive enough for the parameter Mammalian PAPs.

The results of this study and of former studies also show that quantification of PAPs in feed is almost impossible to achieve given the lack of additional information regarding the composition of the PAPs and the corresponding rendering conditions the material underwent. In particular, the quantification of PAPs applying microscopy would require knowledge on the corresponding bone fraction whereas other methods such as immunoassays and PCR would need to have PAPs available that are identical to the PAPs detected in the feed samples and which can be used for calibration purposes.

All methods evaluated in this study did not only demonstrate animal specificity but also tissue specificity which could be an important feature when considering the differentiation between allowed proteins such as milk powder and banned processed proteins. However, the proven tissue selectivity of the test included in this study could necessitate the addition of supplementary information on the label of the test indicating The follow-up of this study will include a ruggedness test focusing on the impact of various parameters such as the feed composition on the outcome of analysis. These additional experiments do not need to be designed as an intercomparison study but can be conducted in a single laboratory. Next to this study, the final step would be conducting a validation by an intercomparison exercise, in which laboratoriespreferably from the feed control field-will analyse the same set of samples.

  ruminant specific tests is extremely important to handle the presence of traces of bones in feed ingredients of plant origin as recently happened in the European Union(European Commission 2005). Due to the current lack of animal specific tests, the sole identification of terrestrial bones can justify the exclusion of the feed concerned from being used in animal nutrition. However, such a decision could be reappraised if a ruminant specific test was able to confirm that the detected residues from animal origin do not derive from ruminant.Another aspect was the impact of organic dicalcium phosphate (DCP) on the detection of PAPs. DCP is permitted in feed for non-ruminant farmed animals and may test positive by immunoassay due to the presence of proteins in it. . We need, however, to place emphasis that such a result would need to be considered as false positive regarding the parameter banned PAPs. Feed samples containing DCP were therefore included in the sample set to examine the impact of the presence of DCP on the control of the MBM ban.The objective of this paper is to present the results of these intercomparison studies conducted in 2004 on behalf of DG Health and Consumer Protection (SANCO). The target parameters for microscopy were (1) "PAPs from all terrestrial animals and fish" (total PAPs), (2) PAPs from terrestrial animals and (3) mammalian PAPs. For the immunoassay methods the target parameters were mammalian PAPs and ruminant PAPs. Though some of the immunoassays included in this study measured also other targets such as PAPs from pig or poultry, we report exclusively on the analytical results due to the particular focus of the sample design on this target.

  immunoassay). The performance characteristics of the methods were therefore calculated based on the number of correct negatives and false positive results of the samples without PAPs and the number of false negative and corrective positive results of the samples containing PAPs at two concentration levels included in the study.

  are the sensitivity indicating the rate of false negative results and the specificity giving information on the rate of false positive results. The following equations were applied: the number of correct positive identifications (positive agreements), NA the number of correct negative identifications (negative agreements), PD the number of false positives (positive deviations) and ND the number of false negatives (negative deviations). The statistics were expressed as percentages after multiplication of the sensitivity and specificity by 100.Since the evaluation of the immunoassays included in this study is based on less data compared to the intercomparison study of the microscopic methods, the analytical results of the immunoassays were expressed in terms of correct positive, correct negative, false positive and false negative results.

  Twelve different samples containing typical compound feed and PAPs from various animals at different concentration levels have been prepared as shown in Table2.The composition was established taking into account the following aspects:Two target concentrations of the processed animal proteins were selected which were (1) 0.1 %, reflecting the sensitivity of the European method as required in and (2) 0.5 % according to a recommendation of the European Commission's Scientific Steering Committee that cross-contamination with mammalian MBM (MMBM) should be condemned at this level (Scientific Steering Committee 1998).

  , beet, straw, molasses, sunflower, palmkernel, coconut, wheat, fat and various feed additives such as minerals and vitamins. The sediment content of the compound feed was about 1.16 % (Standard deviation (SD) = 0.27). Prior to use the material was tested by polymerase chain reaction (PCR), immunoassay kits and nearinfrared microscopy (NIRM) confirming the absence of any interfering substances from animal origin.

  to the laboratory was set at 12 g.

  sediment and are detected by microscopic analysis of the sediment.

  sediment fraction as shown in Figure2.

-

  Evaluation of the official European method as described in Commission Directive EC/2003/126.

  European method as directive EC/2003/126. Eighteen laboratories, including eleven laboratories from new European Member States, reported results of the samples. Two laboratories with major deviations towards the protocol from the Directive were excluded from the study. One laboratory used chloroform as sedimentation agent, another laboratory applied a sedimentation time of 1 minute whereas a minimum of 2x3 min is required for a closed separation funnel (Commission Directive EC/2003/126).

  bone fraction was about 15%.

  study. The characteristics of the immunoassays applied in this study (Table

  Figure 5 shows the results of analysis for immunoassay A, B and C for the test samples MAT VII and MAT VIII. These samples contain ruminant PAPs at the target concentration of 0.1 % (Table 2) but the heat treatment and the protein composition was different since MAT VII contained bovine proteins from various tissues sterilised at 133 °C and MAT VIII contained bovine muscle protein sterilised at 129°C. [Insert Figure 5 about here] Method B turned out to be the most sensitive method, since 9 out of 10 results for ruminant MBM, treated at 133 °C (MAT VII), and all samples from muscle proteins treated at 129°C (MAT VIII) were correctly classified as positive.In contrast, method A failed in correctly classifying the ruminant MBM (MAT VII), since 9 out 10 were false negative results. However, the results of all samples from the (MAT VIII) were correctly positive. Both the lower heat treatment and the different protein composition of both test samples could have been the reason for the positive results on MAT VIII. More specifically, method A was targeted against muscle protein, which coincides with the composition of MAT VIII. The test samples MAT VII, however, was MBM from different animal by-products, thereby containing the target muscle protein of method A at a lower concentration.

For

  most of the materials, the results for the detection of the two-solvent Method are comparable with the results of the Directive EC/2003/126, however the two-solvent Method which fulfils the conditions of the old Directive EC/88/1998 but not of the more strict new Directive EC/2003/126 does not justify a change of the Directive EC/2003/126.The results of the pre-validation of immunassays revealed that the characteristics and performance profiles of immunochemical assays vary considerably between the . Differences exist in respect to the selected animal targets and linked to it the tissue (or organ) range specificity, the taxonomic level of detection and the sensitivity. Method B that measures exclusively a ruminant-specific epitope on a skeletal muscle protein turned out to be the most sensitive test evaluated in this study. It is also important to note that this test identified almost all samples (15 out 16 samples) containing bovine PAPs at 0.1 %. Sufficient sensitivity and selectivity regarding this target is of great importance when considering a modification of the current MBM ban.

  the composition of the PAPs present in the feed. For instance, applying method B requires that the PAPs present in feed also contains proteins from skeletal muscles.

-

  Estonian Veterinary and Food Laboratory, Estonia -Central Veterinary Laboratory, Cyprus -Central Laboratory of National Institute for Agricultural Quality Control, Hungary -National Veterinary Research Institute, Poland -ZHW Szczecin, Poland -Landesanstalt für Landwirtschaft Thüringen, Germany -LUFA -Nordwest, Germany -LUFA -Speyer, Germany -LUFA -Augustenberg, Germany -Bayreisches Landesamt für Gesundheit und Lebensmittelsicherheit, Germany -Veterinary Laboratories Agency Luddington, UK -Seed Testing Station Abbotstown, Laboratory Compex, Ireland -EUROFINS -C R C B, France -Laboratoire DGCCRF de Rennes, France -Laboratoire Fédéral de l'alimentation / AFSCA, Belgium -

Table 4 .

 4 Characteristics of the methods applied in the immunoassay study. Method B utilises the same immunoassay than method A, but applies a different sample preparation procedure thereby obtaining an improved sensitivity.

		Method A	Method B	Method C	Method D
	Target	Ruminant	Ruminant	Terrestrial animals,	All animals,
	PAPs			Ruminant, Porcine,	mammalian
				Poultry
	Target	Skeletal	Skeletal	Muscle, bone and	All animals:
	tissue	Muscle	Muscle	offal	connective tissue
					Mammalian:
					muscle
	Design of	Lateral flow	Lateral flow	ELISA	Lateral flow
	the test	immunoassay	immunoassay		immunoassay

Table 5 .

 5 Performance of methods expressed in terms of sensitivity (%) for PAPs from terrestrial animals.

	Method applied	Study	0.1% MMBM	0.1% MMBM in feed in the
			in feed	presence of 5% fishmeal
	Two-solvent Method	This report	93	60
	European Method	This report	98	72
	(Directive EC/2003/126)
	European Method	Stratfeed	99	77
	(Directive EC/2003/126)	validation study
		(von Holst et al.,
		2005)
	European Method	RIKILT (Van	100	98
	(Directive EC/2003/126)	Ramsdonk & Van
		der Voet, 2003)
	Former European Method	DG-SANCO A	92	44
	(Directive EC/88/1998)	(Gizzi et al., 2004)

Table 6 .

 6 Results of analysis from method D. P = Positive; FP = False Positive; N = Negative; FN = False Negative; NR = No results. Details of the methods are given in

	Blank material	MMBM 0.1%, 133°C + fishmeal, 5%	Fishmeal, 5%	Bovine MBM 0.1%, 133°C	Bovine PAPs 0.1%, 129°C	Porcine PAPs 5%, 133°C	2% DCP
	MAT I		MAT IV		MAT VI	MAT VII MAT VIII MAT IX	MAT X
	FP N NR P FN NR FP N NR P FN NR P FN NR P FN NR P N NR
	0 6 0 0	6	0 0 6 0 6 4	0 0 6 0 10 0	0 0 6 0

Table 2 .

 2 Description of the samples used in the study. MMBM = Mammalian meat and bone meal; DCP = dicalcium phosphate; Concentrations are expressed in terms of percent of mass fraction. Total number of samples per laboratory was 24 for microscopy and 50 for immunoassay analysis.

	MAT	MAT	MAT	MAT	MAT	MAT	MAT	MAT	MAT	MAT	MAT	MAT
	I	II	III	IV	V	VI	VII	VIII	IX	X	XI	XII
	MMBM, 133°C (%)

Determination of processed animal proteins in feed: the performance characteristics of classical microscopy and immunoassay methods

  -

	The detection of traces of PAPs including meat and bone meal (MBM) in feed is still a EC/2003/126 is superior to the method as described in Commission Directive
	Introduction
	challenging task. Laboratories apply various methodological approaches for the EC/88/1988 which allows more variability of the protocol applied. For instance, a very
	The required sensitivity and selectivity of analytical methods applied to the detection of detection of MBM, but a former intercomparison study (DG SANCO 2003) showed that challenging task is the detection of terrestrial MBM at 0.1 % in the presence of 5 % of
	processed animal proteins (PAPs) in feed are specified, taking into account current and classical microscopy is still the most reliable tool compared to polymerase chain fishmeal. These levels have been selected taking into account the current requirements
	up-coming European legislation regarding the use of PAPs in animal nutrition. Focusing reaction (PCR) and immunoassays (Gizzi et al. 2004). In addition, a more careful for analytical methods applied in feed analysis for this purpose as outlined in the
	Microscopy: Number of samples per laboratory Immunoassay: Number of samples per laboratory F 3 6 o 3 -r 3 -F o r on the BSE-related aspect, EC Regulation 999/2001 prohibits the use of mammalian 3 3 3 ----3 3 6 -6 10 6 10 6 --PAPs in ruminant feed. General rules regarding the safe use of animal by-products are laid down by EC Regulation 1774/2002, prohibiting feeding of animals with processed F o r examination of the results from the laboratories applying microscopy revealed that quite different protocols for the microscopy were applied, which where all covered by the European method valid until 30 June 2004 (Commission Directive EC/88/1998). chapter "Experimental" of this paper. The pooled results from the various microscopic F protocols that were covered by the former official method (Commission Directive o r EC/88/1998) revealed a rate of correct positive detections of 45 %. In contrast, the Mean Ct with 2 x SD interval (and targeted animal species) ---33,21 ± 2.01 ( cattle) --34,77 ± 2.29 (cattle) 33,89 ± 1.96 (cattle) ----Deleted: chicken P P P P validation of the microscopic method as described by Commission Directive
	e e r e e r e e r Since 2001 the European project "Stratfeed" (STRATFEED EC project 2001) was working on the development and validation of analytical methods based on PCR, e EC/2003/126 confirmed a significant improvement since the rate of correct positive e r results increased to about 77 % (von Holst et al. 2005).
	R R R spectroscopy and microscopy proposing a modified protocol for microscopy. R
	e e e Comparing the results of the Stratfeed project with the results from the DG SANCO e
	v i e v i e v i e 2003 study demonstrated that the protocol parameters of the microscopic method applied by the best performing laboratories coincided partly with the Stratfeed protocol v i e
	w w w indicating the superiority of the latter method. Based on the results from the DG w
	O n l y O n l y O n l y SANCO 2003 study the European Commission discussed with Member States' experts a revision of the European method (Commission Directive EC/88/1988) leading to a O n l modified protocol (Commission Directive EC/2003/126) which also reflects the method modifications proposed by the "Stratfeed" project. The modified protocol is the only y
	official European method since 1 st July 2004 and has been recently validated by an
	intercomparison study (von Holst et al. 2005). Comparing the results of this study with
	the results of DG SANCO 2003 study (Gizzi et al. 2004) corroborated that the
	sensitivity of the more specified method as required by Commission Directive
	4 5

C. von Holst 1* , A. Boix 1 , V. Baeten 2 , J. Vancutsem 3 , G. Berben 2 e-mail: christoph.von-holst@cec.eu.int * corresponding author proteins from the same species. Enforcing these regulations would therefore require that analytical methods are capable of specifically detecting mammalian PAPs, PAPs from pigs and from poultry. The latter aspect is important to avoid intra-species recycling.

Since BSE is linked to the presence of ruminant PAPs in ruminant feed, the specific detection of ruminant PAPs is also extremely important.

However, due to various problems such as the lack of methods that fulfil the above mentioned criteria, EC Regulation 999/2001 was amended by EC Regulation 1234/2003 introducing a ban on almost all PAPs in animal nutrition. It is important to note that this Regulation clearly indicates the need for a reappraisal of the total MBM ban once new and more specific control methods are available. In particular, there is a strong need for ruminant specific tests in order to establish whether traces of MBM in feed or feed ingredients that are most likely present in the material due to cross contamination contain ruminant PAPs. An overview of the current legal situation regarding the use of PAPs is given in Table

1

.

[Insert Table

1

about here]

  Table 6 about here]

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

European Commission, Directorate General Joint Research Centre, Institute for

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

Acknowledgments

The authors would like to thank the European Commission Direction General Health and Consumer Protection for financial support for this study.

The authors thank Isabelle Fissiaux, Felix Rwagasore and Olivier Fumière for the preparation and testing of the homogeneity of the samples.

In addition the authors are grateful to the following laboratories and institutes which participated in the intercomparison study: -National Veterinary Institute (NVI), Slovenia -State Veterinary and Food Institute, Slovak Republic -Central control and testing institute of agriculture, Slovak Republic -Central Institute for supervising and testing in agriculture, Czech republick -State Veterinary Medicine Diagnostic Center, Latvia -National Veterinary Laboratory, Lithuania

, Vincent; Wallloon Agricultural Research Centre (CRA-W), Quality of Agricultural Products Department Vancutsem, Jeroen; Federal Agency for the Security of the Food Chain (AFSCA-FAVV) Berben, Gilbert; Wallloon Agricultural Research Centre (CRA-W), Quality of Agricultural Products Department

Available from: http://stratfeed.cra.wallonie.be Van Raamsdonk LWD, van der Voet H. 2003. A ring trial for the detection of animal tissues in feeds in the presence of fishmeal. Report 2003.012. RIKILT. Wageningen. pp. 17 with 6 addenda.


Laurence Castle

Andy Hart

Mel J Holmes

Peter Kenneth

Thomas Oldring
email: peter.oldring@valspareurope.com

P K T Oldring

AN APPROACH TO STOCHASTIC MODELLING OF CONSUMER EXPOSURE FOR ANY SUBSTANCE FROM CANNED FOODS USING SIMULANT MIGRATION DATA

Keywords: migration, exposure, threshold, canned foods, metal closures (lids) 21 22

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

The purpose of this study was to investigate how the extent of consumer exposure to a 2 generalised chemical migrant from food packaging materials may be estimated using 3 migration data obtained with food simulants. We have used a 2-dimensional probabilistic 4 Monte Carlo model [START_REF] Holmes | Dietary Exposure to Chemical Migrants from food 30 contact materials: a probabilistic approach[END_REF]] with, as a test case, the migration of an arbitrary 5 substance from coated light metal packaging. 'Light metal packaging' encompasses food 6 cans, aerosols, tubes and closures such as lids and tops. Single-point estimates and 7 deterministic estimates of exposure to selected migrants from can coatings have been made by 8 others, e.g. for bispenol A diglycidyl ether [SCF, 2002a] and for bisphenol A [SCF 2002b], 9 but this is the first application of probabilistic modelling. We have tackled this question in 10 two ways. In the first, the exposure that would result from a given level of migration into a 11 food simulant is estimated. In the second approach, using the procedure in reverse, the 12 maximum migration that could be tolerated in order to keep consumer exposure below a pre-13 defined threshold is calculated. 14 15

The normal approach used by the EU Commission for assessing potential exposure to 16 migrants from packaging, takes a default assumption that an average 60kg individual 17 consumes 1 kg of packaged food each day, that this packaged food is always packed in the 18 material of interest, that the packaging material always contains the substance under 19 consideration, and that the substance is always released from the packaging into the food at 20 the maximum migration limit for that substance [START_REF] Barlow | The role of the Scientific Committee for Food in evaluating plastics 3 for packaging[END_REF][START_REF] Ceu | Note for guidance of petitioner when presenting an application for safety 18 assessment of a substance to be used in food contact materials prior to its authorisation[END_REF]]. This exposure 21 model is generally conservative, in that it overestimates exposure in most cases. The default 22 assumptions are used not because they are thought to be realistic, but because in the absence 23 of any other information, this exposure model is generally accepted to be a worst-case for 24 most packaging applications. 25 Previously, a joint industry group for light metal packaging used a per capita approach 2 [START_REF] Dionisi | Estimates of per capita exposure to substances 26 migrating from canned foods and beverages[END_REF] to estimate exposure to migrants from canned foodstuffs. Their 3 calculations used statistics for: i) the number of cans manufactured in Europe per year, ii) the 4 different food types that these cans were used for, iii) the corresponding surface area for each 5 type of foodstuff, iv) corrections for imports and exports, and v) typical migration levels into 6 foods. It is clear that that such a per capita approach will under-estimate exposure, because a 7 simple averaging procedure is used and no distinction is made between high, low and non-8 consumers of canned foodstuffs. The present study represents a refinement of exposure 9 estimates, now using actual food consumption statistics and better estimates of packaging 10 usage. We have used UK food consumption statistics to illustrate this approach. One future 11 task would be to use statistics for other countries, to see first how easily the statistics could be 12 harnessed in this way and, second, how the estimates compare for different countries. 13 14 A sample representative of the UK population was obtained using the detailed food 15 consumption records of three UK National Dietary and Nutrition Surveys (NDNS) [UKDA, 16 1990;1998;[START_REF] Ilsi | Threshold of Toxicological Concern for Chemical Substances Present in the Diet[END_REF]. The surveys provide only limited information on the packaging materials 17 used for each of the food items. To address this information gap, market share (with 18 uncertainty) information on food/package combinations were used here. In the following 19 sections we provide a model overview, describe the data inputs, the process of associating 20 specified food items with the migration concentration data used, and finally the results 21

MODEL OVERVIEW 1

A detailed description of the stochastic model used has been published [START_REF] Holmes | Dietary Exposure to Chemical Migrants from food 30 contact materials: a probabilistic approach[END_REF]. 2

In outline, the daily dose (DD) expressed in µg/kg bw/day is calculated using equation 1.

3 = = ) ( 1 1 k n l ijkl ijkl j ijk c w W DD Equation 1 4
Here, DD ijk is the daily dose during iteration i of the model, for individual j on day k 5 consuming up to n(k) items on that day. W j is the weight of individual j and c ijkl is the 6 concentration of the migrant in the food commodity l whose weight is w ijkl . Depending on 7 the survey duration we calculate the average daily dose for each individual j. For each 8 iteration i uncertain parameter values for the descriptive distributions are sampled, these are 9 then fixed during the subsequent calculations of the exposure for each individual. Exposure 10 across individuals (within an iteration) will vary due to consumption, packaging type and 11 concentration within the food. Exposure for a specific individual (across iterations) will vary 12 due to the packaging type and concentration within the food. 13 14 For this test case therefore, the main tasks were to decide which of the food items in the diary 15 records were packaged in coated light metal packaging, what the consumption of these food 16 items was, and what was the migration concentration data for these food items, leading to a 17 where duplicate descriptions occurred we ensured that they were categorised in the same 13 group-subgroups. At the most detailed level there are individual food item descriptions, in 14 some cases with indications of the packaging type. For example, food item 'sweetcorn, 15 canned, drained'. In the 3 surveys there were 884,272 food items consumed in total, covered 16 by about 11,000 different items descriptions when recipe descriptors were included. 17 18

Composite foods and Recipes 19

Some food item descriptions indicated that they are a combination of individual food types, 20 e.g. pre-prepared meal or, due to the preparation or processing, are a combination of food 21 types, e.g. 'Tuna and pasta bake with canned tomatoes and olives'. Clearly, in order to 22 estimate exposure the contributions from the differently-packaged components must be 23 included. To address this issue the NDNS food item codes are identified as whole foods or 24 recipes. Many of the recipes are described in the Risk Recipe Database (RRAD -unpublished 25 proportions in which they occur. For recipes not found in the RRAD a conservative estimate 2 was made of the proportions of each ingredient and the extrapolation factor (see later) was 3 used to account for this. The total number of food items with discrete descriptions consumed 4 in the surveys, following recipe deconstruction etc., was reduced to ca. 4,200. 5 6 Observations from raw survey data 7

The raw data in the NDNS surveys was interrogated to determine what could be understood 8 about the consumption habits of the UK public with regard to consumption of canned food 9 and beverages. This was independent of any stochastic modelling of consumption and 10 potential exposure to migrants. The average daily consumption of food and beverage 11 independent of packaging was calculated for each of the 3 age groups. For adults it was 2.9 kg 12 of food and beverage per person per day, very similar to the value of 3 kg used by the USFDA 13 [START_REF] Cheeseman | A tiered approach to 23 threshold of regulation[END_REF]Munro et al. 2002]. Seniors (>65 years) consumed 2.25 kg 14 whilst Youths (4 to 18 years) consumed 1.7 kg/person/day. The average number of different 15 items of food and beverage consumed daily was 25 for youths, 36 for adults to 39 items per 16 person per day for seniors. The eating habits of the three age groups are different. It should 17 also be noted that dietary habits may, and probably will, have changed since the surveys were 18

conducted. 19 20

To determine the level of consumption of canned food and beverages, all items that were 21 described as canned or were almost certainly canned (e.g. corned beef) were placed into 3 22 groups. These were canned beverages, canned foods and canned foods that formed part of a 23 meal. Only 17 out of 2197 (0.8%) of adults did not consume a canned item (food or 24 beverage) during the survey period. Similarly, only 92 out of 1687 (5.5%) Seniors and 6 out 25 of 1701 (0.4%) youths did not consume canned items during the survey periods. The average 1 weight of food and beverage, explicitly recorded in the surveys as being canned, consumed by 2 seniors was 0.13 kg/person/day, 0.18 kg for adults and 0.17 kg for youths. This was for actual 3 consumers (non-consumers were not included). Table 2

Migrant concentration data 1

All relevant food items that are identified and consumed within the dietary surveys must be 2 associated to their migration data. Food simulants are used to test for the general case, for 3 contact with a variety of foods of the same or similar class, and so in this treatment for any 4 generic migrant we have set up the model to use food simulant migration data. There are no 5 food simulants explicitly listed in EU regulations for testing polymeric coatings on light metal 6 packaging, but for plastics the simulants listed in Table 3 are specified according to the type 7 of food that is intended to be packed [START_REF] Ceu | Commission Directive 2002/72/EC relating to plastics materials and articles 10 intended to come into contact with foodstuffs[END_REF][START_REF] Ceu | Corrigendum to Commission Directive 2002/72/EC of 6 August 2002 relating to 14 plastic materials and articles intended to come into contact with foodstuffs[END_REF]]. 8

{insert Table 3

about here} 9

Migration data for simulants are generally reported on a surface area basis in units of µg/dm 2 .

10

In this study we consider an arbitrary migrant with a migration level of either 0 or 10 µg/dm 2 11 into the aqueous simulants A and B (distilled water for aqueous foods; 3% acetic acid for 12 acidic foods) and for simulant D (fatty foods). Beverages were excluded from this evaluation, 13 as their can coatings tend to be specific to beverages. Since this study is restricted to foods 14 and not beverages the simulant C (10% ethanol solution, for alcoholic beverages) is not 15 considered. The Plastics Directive [START_REF] Ceu | Commission Directive 2002/72/EC relating to plastics materials and articles 10 intended to come into contact with foodstuffs[END_REF][START_REF] Ceu | Corrigendum to Commission Directive 2002/72/EC of 6 August 2002 relating to 14 plastic materials and articles intended to come into contact with foodstuffs[END_REF] allows for a correction of simulant D 16 migration data by a reduction factor to account for the aggressive character of simulant D 17 (olive oil) compared to most fatty foods. However, for can coatings where the food is 18 retorted, it can be argued that these reduction factors are questionable because the severe heat 19 processing conditions that the thin polymeric coating experiences, can give rise to exhaustive 20 migration even with low-fat foods. So the model was run both using and then not using these 21 reduction factors, which are in the range 2-5. In the model, the corresponding simulant and a 22 reduction factor if applicable, was assigned to every item of foodstuff recorded in the surveys.

Conversion factors 1

When migration levels are expressed per unit surface area (i.e. µg/dm 2 ) the EU standard 2 conversion to a mass basis is achieved by a multiplication with the factor 6dm 2 /kg, for a 3 standard 10 by 10 by 10cm packaging cube of a food with density of 1. However, it is 4 apparent that the actual packaging types can cover a range of contact scenarios where this 6:1 5 ratio is inappropriate. Improved conversion factors (CF) for the surface area/mass ratios were 6 calculated using the actual ranges encountered for the different can sizes. 7

Can sizes (contents mass and surface area) with their market shares by country [Dionisi et al. 8 2002] were averaged for each food type (including beverages). Three size ranges were 9 established which encompassed all of the food types and these are shown in Table 4. The 10 food types of fruit, vegetables, soups, dairy produce, ready meals and other foods all had a 11 similar range and were defined as 'Regular'. Meat and fish had distinctly higher ranges. [START_REF] Barlow | The role of the Scientific Committee for Food in evaluating plastics 3 for packaging[END_REF] The can sizes for beverages may range from 150ml -500ml with respective surface areas of 13 1.8 -4.1 dm 2 . These values gave a conversion factor in the range 8 to 12 dm²/kg, thus 14 beverage cans were assigned 'Regular' conversion factors. 15

For closures (i.e. lids on bottles and jars), two main sizes were allocated (small and large) 16 with conversion factors representing the ranges typically found. This reflects the significantly 17 smaller surface areas found when mixed packaging is considered. Similarly, conversion 18 factors for tubes and aerosols were also be calculated. The values used are given in Table 4.

{insert Table 4 about here} 20 21

Extrapolation factors 22

In some cases the concentration data do not correspond directly to the food item description. 23

As an example consider the food item 'corned beef hash'. Assuming that the corned beef was 24 canned (i.e. 100% market share), if a dietary record showed that a person consumed 100g of 25 corned beef hash, it is clear that they did not consume 100g of canned corned beef. In this 1 case, and in the absence of recipe information from the RRAD (see above) it was estimated 2 that the amount of corned beef in the recipe was 50%, ranging from 30% to 70%. To allow 3 for this, an extrapolation factor (EF), defined as a triangular distribution with range [0.3, 0.5, 4 0.7] was used to correct the total recipe weight to a mass of canned corned beef consumed. 5 6

Market share 7

In order to calculate the dose due to the migrant in a particular food item we must establish 8 the packaging type. In the case of canned foodstuffs, often the NDNS food item descriptions 9 enable the packaging type to be identified directly, i.e. are definitely packaged in metal e.g. 10 'Custard, low fat canned'. For these items the market share is 100%. For those items 11 definitely not packaged in coated metal, then the market share is 0%. Example 'salmon, raw ' 12 or 'grape juice carbonated not canned' and so these items do not contribute toward the 13 exposure. 14 15 For the remaining food items, whilst the market shares of different packaging types are 16 known at a manufacturing level, in most cases detailed information at the level of each 17 individual food item is not available. For these cases it is necessary, using expert judgement, 18 to estimate the market shares (with uncertainty) of the packaging(s) of interest, e.g. 20±20% 19 can, 25±20% large closure, 25±20% small closure and 30±20% other. This information 20 would then be sampled from a triangular distribution with range [0, 0.2, 0.4] etc. 21

22

Packaging Loyalty 23

Packaging loyalty is indicated if the individual's consumption of a given package type is 24 greater than would be expected from market share. Consumers who exhibit loyalty will have 25 -13 -higher exposure. To explore the importance of packaging loyalty we adopted two options, 1 zero package loyalty and total package loyalty. Zero package loyalty, as it's name suggests, 2 indicates that a consumer will choose an item with a specific package type with proportions 3 equal to the market shares of the package types, i.e. shows no bias toward any one package 4 type. In contrast, total package loyalty is where an individual will always choose an item with 5 the same package type. For example, they will always tend to choose a particular food 6 product in a metal can in preference to a plastic pouch or a glass jar, or vice versa. Clearly, 7 packaging loyalty is linked to brand loyalty. To implement package loyalty, we applied it at 8 the food group level and fixed the package type of the food items contained within that group 9 to that of a random sample from the package types using the market share values. This is a 10 simplification that removes the need to apply loyalty to each food item consumed. In fact this 11 has an added advantage because even if packaging loyalty was applied to each item, it would 12 be expected that to some extent the same packaging loyalty would operate across similar food 13 items. 14 To manage the large number of individual food items, they were gathered together into 6 groups for which the same parameters applied; regarding packaging type, concentration data, 7 conversion factor, extrapolation factor, market share, etc. It is possible to group at a high 8 (coarse) level, with many items in a few groups, or at a low (detailed) level with a few items 9 in many groups. The lowest level grouping required inspection and grouping of 4,200 10 individual items. The approach used was to select those items which were definitely canned 11 (100% market share) and those which were definitely not canned (0% market share). Expert 12 judgement was used to allocate a market share for the remainder. The items which were, or 13 could possibly be, canned were then further sub-divided and grouped. This grouping was at 14 various levels and in some cases was according to type of foodstuff (simulants), type of 15 container (can, closure, aerosol, tube), size of can (fish or regular, for example) or closure, 16 part or whole of meal as outlined earlier. 17 The different groups which form the basis for the models are given in Tables 5 and6, where it 19 can be seen that the low level (detailed) grouping consisted of 66 groups compared to 4 20 groups for the high level (coarse) groupings. The more refined the segregation into groups 21 the more realistic the assumptions, because specific and different factors can be applied to 22 each group. Runs denoted by T1, T2 or T3 were based on the high level grouping, whilst the 23 others (T4, T4 and T5) used the low level grouping. For the low level groupings, items were identified which could be in a can or jar. For 3 example, sauces could be in a can (high surface area) or jar (relatively low surface area of lid). 4

A conservative assumption of 50% market share (with an associated uncertainty distribution) 5

for sauces being in a can was made, with jars having the remaining market share. For this case 6 it was assumed that none were packaged in plastic. Table 7 illustrates how data were 7 associated for a foodstuff, which could be in a jar or can. In other cases it was possible that 8 some of the food could be packaged in alternative forms of packaging, such as retort plastic. 9

A market share representing a conservative case (highest usage) for metal packaging, with an 10 associated range, was allocated. In Table 7 packaging can be used to estimate exposure to that substance using the CSL stochastic model 23 [START_REF] Holmes | Dietary Exposure to Chemical Migrants from food 30 contact materials: a probabilistic approach[END_REF]. Various scenarios about a migrant into foodstuffs were used in order to 24 compare their impact on the exposure. These scenarios covered the nature of the migrant (e. The "definitely not canned" group, vitamins etc, as well as beverages were not associated with 18 any concentration data and were therefore not used in any of these evaluations. Beverages 19 were excluded from this evaluation, as their can coatings tend to be specific to beverages. 20 and aerosols. Furthermore, the migration was at a single fixed value thus variation between 8 level of detection and the fixed value was not used. Migration into A, B, C was a true zero, 9 thus they did not contribute to exposure from the groups assigned to simulants A, B, C or O. 10 However, if two simulants are representative for a particular foodstuff, such as (B, D/3) (a 11 food both acidic and fatty) then that item was allocated the D concentration data. The 12 differences in T1 to T5 are: 13 14 T1 (high level) assumed that the simulant D reduction factor was not applicable and migration 15 was at 60 µg/kg. 16 17 T2 (high level) assumed that the simulant D reduction factor was not applicable and migration 18 was at 10 µg/dm². In addition a conversion factor to represent the different sized containers 19 was applied and due to the coarse grouping, a wide range was used [0.08, 6, 19] dm²/kg. 20 21 T3 used the same assumptions as T2 but the simulant D reduction factor was applied. 22 23 T4 (low level) assumed that the simulant D reduction factor was not applicable and migration 24 was at 10µg/dm². Conversion factors appropriate for the different sized packages were 25 applied. 26 27 T5 (low level) assumed that the simulant D reduction factor was not applicable and migration 28 was at 60 µg/kg. 29 30 T4-D, T4-AB, T4-ABD (all low level) were models for canned foods only (aerosols, tubes 31 and closures were excluded) and assumed that the same coating would be used for all the 32 canned food items. It was assumed that the substance only migrated into D foods (T4-D) with 33 A and B foods being a true zero or vice versa (T4-AB) or the substance migrated equally into 1 all foods (T4-ABD). In those instances where a food item could be allocated more than one 2 simulant, such as (B, D/3), then depending on the above scenario the migration was allocated 3 either that for B or D. In both these cases, the actual value was the same, thus that food item's 4 contribution to exposure was the same since the simulant D reduction factor was not used in 5 these runs. Migration was a single fixed value of 10 µg/dm². 6 7 Exposure 8 9

The results from the above eight models run for the 97.5 percentile consumer for each age 10 group are shown in Table 8. The data are in µg per kilo body weight (actual) per day -µg/kg 11 bw/day -or µg/person/day and are for the three age groups, youths, adults and seniors. 12 13 {Insert Table 8 about here} 14 15 Considering models T1 to T5, initially, the following can be concluded. 16

17

• The use of a simulant D reduction factor reduces the exposure by a factor slightly 18 greater than 2 (T2 cf T3) from (0.1 -0.22) to (0.05 -0.09) µg/kg bw/day. 19 20

• Refining the groupings (T2 cf T4 and T1 cf T5) reduces the exposure, but only slightly 21 from (0.1 -0.22) to (0.11 -0.17) and (0.07 -0.16) to (0.06 -0.1) µg/kg bw/day. 22

23

• Using µg/dm² instead of µg/kg of food increases the exposure (T1 cf T2) (0.07 -0.16) 24 to (0.1 -0.22) (T4 cf T5) (0.11 -0.17 As can be seen in the Table 7 andFigure Considering Table 8, it can be seen that the main contributors to exposure from canned foods 24 are those represented by simulants A or B (T4-AB). This is about 3 times greater than those 25 foodstuffs represented by simulant D (T4-D) 0.26 -0.52 cf 0.11 -0.17 µg/kg bw/day. It is 26 not surprising when one considers the types of food and their consumption. The results for 27 migration into A, B plus D (T4-ABD) does not equal the sum from the other two models, due 28 to the fact that some foods consumed were allocated mixed simulants, such as B, D/3 and they 29 would have contributed to exposure in both models T4-AB and T4-D.

Derivation of a threshold migration level 1 2

Coated metal packaging, like other forms of packaging, may give rise to a number of migrants 3 at low levels that are neither starting substances (monomers) or additives [START_REF] Ilsi | Exposure from food contact materials[END_REF]. It is 4 practically impossible to identify, isolate or synthesise, and assess the hazard of each and 5 every one using conventional toxicity tests. This situation is not unique to packaging 6 migrants and a generalised approach to deal with the issue has been proposed. The threshold 7 of toxicological concern (TTC) is a principle which refers to the establishment of a generic 8 human exposure threshold value for chemicals below which there would be no appreciable 9 risk to human health. [START_REF] Ilsi | Threshold of Toxicological Concern for Chemical Substances Present in the Diet[END_REF]KROES et al., 2004;[START_REF] Barlow | Threshold of toxicological concern (TTC): A tool for assessing 6 substances of unknown toxicity present at low levels in the diet[END_REF]. For chemical 10 migrants from food contact materials, the US-FDA uses a threshold exposure of 1.5 ug per 11 person per day [MUNRO et al., 2002] and we shall use this value for the purpose of 12 illustration here. 13 14 It is possible from the exposure resulting from migration at 10 µg/dm² to estimate the level of 15 migration corresponding to an exposure ceiling of 1.5 µg/person/day for the 97.5%-ile for the 16 scenarios represented above, as shown in Table 9. It should be borne in mind that this 17 assumes that the only source to exposure of the substance is from canned fatty foods. 18 the traditional 6dm²/kg used by the EU. The range used was from 6 to 19 dm 2 /kg (Table 4). 1

This threshold level of migration is still a conservative estimate due to the fact that different 2 coatings are used for different foodstuffs and the species migrating from one could be 3 different to those from another. In order that a more refined estimate for a migration 4 corresponding to a threshold is obtained it would be possible to consider the individual 5 coatings and their likely migrants into different foods on a case by case basis. It should also 6 be recognised that these estimates for the 97.5 th percentile consumer are based on 4-or 7-day 7 food diary records and chronic exposure would be expected to be lower over longer periods of 8 time. 9

  communication) which break-down the recipe into its ingredient and the 1

  18

  , the group contains foods represented by simulant 11 D/4 packaged in either cans or jars. The conversion factors of [7, 11, 19] represent the surface 12 area to weight range for meat cans and [0.35, 1.2, 4.0] represents that for large closures (lids). 13Each package type was assigned a 50%± 25% market share. The extrapolation factor is 0.25 14 because the foodstuff is simulant D/4 and the simulant D reduction factor was applied for this 15 particular run. If it were not then the extrapolation factor would be 1case, migration of a substance into different simulants from light metal 22

  g. 25 only fat-soluble, only water-soluble etc) and the availability of migration data on a 26 concentration-or area-related basis. 27 1. A species migrated into fatty foodstuffs (simulant D) only and that migration into 28 foodstuffs represented by simulants A, B and C was a true zero 29 simulant D reduction factor was or was not applicable 2 3 3. Migration was either at 10µg/dm² or 60µg/kg 4 5 4. Migration into simulant D foods, which are in cans only, with migration into A, B and C 6 being a true zero . 7 8 5. Migration into simulant A or B foods, which are in cans only, with migration into D 9 being a true zero . 10 11 6. Migration into simulant A or B or D foods, which are in cans only. 12 13 either because migration does not occur into that food/ simulant type or, more fundamentally, 14 because different coating chemistries are used for different food types, which do not contain a 15 residue of the substance. 16 17

  the model were used to represent the above scenarios. 5 6 T1 to T5 considered migration only into simulant D foodstuffs packaged into cans, jars, tubes 7

Figure 1

 1 Figure 1 displays these results in units of g/kg-bw/day for the 97.5 th percentile consumer, 27 together with the 95 th -percent (2 standard deviations) confidence range on the uncertainty 28 associated with the inputs. 29 30 {insert figure 1 about here} 31 32

  1, the model T2 produces the highest exposure 5 assessment across all of the surveys with the greatest uncertainty due to the conservative 6 uncertainty range imposed on the conversion factors. T3 indicates a proportionate reduction 7 by the introduction of the simulant D/X reduction factors. Model T4 illustrates that 8 examining individual food items and associating more appropriate conversion/extrapolation 9 factors to the refined groups, has the effect of reducing the exposure estimates and reducing 10 the associated confidence range of the estimate. Model T5 is equivalent to model T1 but uses 11 the refined baskets. This indicates how an exposure estimate is reduced by applying more 12 accurate associations to the concentration data. 13 14 Contributors to exposure 15 To explore what factors are involved within these models, additional analysis is required. An 16 obvious property to investigate is the percentage contribution of each of the food baskets, for 17 example for the model T2 this is shown in Figure 2. As can be seen, the primary contribution 18 of the exposure comes from the basket for items assigned simulant B, D which contained 19 canned vegetables i.e. highest consumed items. 20 21 {Insert Figure 2 about here} 22 23

  reduction factors, an exposure of 1.5 µg/person/day equates to a 22 migration limit of 1.83 to 2.61 µg/dm² (T2 and T4). 23 24 With the use of simulant D reduction factors this is increased to 4.02 to 4.95 µg/dm². 25 26 Migration at 15 to 19 µg/kg (T1) or 22 to 28 µg/kg (T2) corresponds to an exposure of 1.5 27 µg/person/day. 28 29 Not unexpectedly if a substance migrates at 10 µg/dm² into all foods represented by simulants 30A, B and D, or A and B then the migration threshold is low being < 1 µg/dm². However, if 31 migration occurs only into those foodstuffs represented by simulant D, then a threshold of 32 about 2 µg/dm² is possible. Note that this is for the actual surface areas encountered and not 33

  by: Association of European Producers of Steel for Packaging (APEAL), 3 PlasticsEurope, European Council of Paint, Printing Ink and Artists' Colours Industry 4 (CEPE), Confederation of European Paper Industries (CEPI), European Aluminium 5 Association (EAA), European Phenolic Resins Association (EPRA), Ecological and 6 Toxicological Association of Dyes and Organic Pigments (ETAD), European Wax Federation 7 (EWF), Food Contact Additives Panel (FCA), Flexible Packaging Europe (FPE), European 8 Secretariat of Manufacturers of Light Metal Packaging (SEFEL). The statements and 9 conclusions in this paper are the responsibility of the authors alone and they should not be 10 taken to represent the opinion of the sponsors of this work.

Figure 1 .

 1 Figure 1. This graph shows the 97.5 th -percentiles for the different age groups for the different threshold models run. Red diamonds indicate the median values as shown in Table8and the red lines give the 95 percent confidence range for each estimate.

Figure 2 .

 2 Figure 2. Percentage contribution to the exposure from the food baskets as defined in model T2 for the youth survey. Again diamonds indicate median values and lines denote the 95 percent confidence range.

  For this work the NDNS food code list was re-organised into 21 main food group headings 9 such as Bread, Carcass meat and Milk. Each group was then further subdivided, e.g. White 10 bread, Wholemeal bread etc, giving 114 sub-groups. During this stage the food codes were 11 checked to ensure they had been correctly assigned in the NDNS structure. Additionally, 12

	1	DATA INPUTS
	2
	3	Food consumption data
	4	In each of the NDNS surveys (Table 1) the food consumption of about 2000 individuals is
	5	recorded for a 4-or 7-day period. Approximately 4200 individual food item descriptions are
	6	used in the surveys.
	7 8	F o r Food item hierarchy.	{insert Table 1 about here}
		P
		e
			e r
			R
			e
			v i e
			w
	18	distribution of exposure estimates.	O n l
	19			y
	20

Table 1 .

 1 MUNRO, I. C., HLYWKA, J. J., & KENNEPOHL, E. M., 2002. Summary of the NDNS surveys used in this paper. 1

	Risk assessment of

Table 3 .

 3 Food simulants specified for testing plastics for migration (CEU 2002, CEU 2003) 7

	Simulant	Composition of the	Foodstuffs that the simulant represents
	code	simulant
	A	Water	aqueous foods with a pH > 4.5
	B	3% w/v Acetic acid	Acidic foods pH <= 4.5
	C	10% v/v Ethanol	Alcoholic foods & beverages
	D	Olive oil or alternative	Fatty foods
	(D/X *)	fat simulants	* Test value divided by reduction factor X,
			in the range 2 to 5, because olive oil is too
			severe for less fatty foods
	O	No testing required	For example fruits with a peel
	8
	9

Table 4 .

 4 Surface area to weight (dm²/kg) ratios for different types of cans and packaging for

	1
	2	food.
	3
			Lowest	Median	Highest
		Can use
		Regular (R)	6	8	12
		Meat (M)	7	11	19
		Fish (F)	14	17	19
		Closure Type
		Small (S)	0.08	0.2	0.8
		Large (L)	0.35	1.2	4.0
		Tubes	10	13	16
		Aerosols	12	14	16
	4
	5

Table 5 .

 5 Low level (detailed) groups definitions used in model T4 and T5. 1

	Group Description	No. of items Group Description	No. of items
	100% not canned	3167	Can R/closure L (50/50) 100% M/S sim D/5	5
	Small closure 75% M/S sim O	1	Can R/closure L (50/50) 100% M/S sim B	5
	Small closure 75% M/S sim D/3	15	Can+can/closure in meal 100%M/S EF0.5 sim B	8
	Small closure 75% M/S sim B	12	Can tom 100% M/S EF 0.2 sim B	6
	Small closure 75% M/S sim A	14	Can R/closure L (50/50) 50% M/S sim D/4	1
	Sauce closure 100% M/S sim O	1	Can R /closure L (50/50) 100% part meal sim B	22
	Possibly can M 30% M/S sim D/5	55	Can meat meal 100% M/S EF 0.5 sim D/4	10
	Possibly can M 30% M/S sim A, D/4	3	100% canned items sim D/5	7
	Possibly can 50% M/S sim D/5	5	100% canned items sim D/4	19
	Possibly can 50% M/S sim D/4	4	100% canned items sim D/3	7
	Possibly can 50% M/S sim D/2	2	100% canned items sim D	9
	Possibly can 50% M/S sim B,D/3	1	100% canned items sim C*	9
	Possibly can 50% M/S sim B	6	100% canned items sim C	13
	Possibly can 50% M/S sim A	28	100% canned items sim B, D/3	9
	Possibly can 30% M/S sim O	5	100% canned item sim B	90
	Possibly can 30% M/S sim D/4	5	100% canned item sim A, D/4	7
	Possibly can 30% M/S sim D/3	2	100% canned item sim A	65
	Possibly can 30% M/S sim B, D/5	5	Tubes simulant D/3	1
	Possibly can 30% M/S sim B	1	Tubes part of meal Sim B	2
	Possibly can 30% M/S sim A	4	Tubes B, 100% MS	6
	Large closure 50% M/S sim D/5	1	Tube simulant A	2
	Large closure 50% M/S sim D/4	2	Simulant B, part of closure sauce only L	2
	Large closure 50% M/S sim D/3	13	Sim B canned 100% part of meal	2
	Large closure 50% M/S sim A, D/4	12	Large closure D/5 M/s 50% part of meal	14
	Large closure 50% M/S sim A	6	Closure S part of meal 50%MS sim B EF 0.1	2
	Large closure 100% sim D/5	1	Closure L Sim B 50% M/S	3
	Large closure 100% M/S sim O	1	Can closure 50/50 part of meal simulant B	4
	Large closure 100% M/S sim D/3	6	Aerosol D/2 100% M/S	1
	Large closure 100% M/S sim D	1	100% canned fish sim D/3	3
	Large closure 100% M/S sim B	31	100% canned fish sim B,D/3	6
	Large closure 100% M/S sim A	12	100% canned fish sim A	20
	CanR/closureL 50% M/S sim B, D/5	1	Vits medicines & toddlers	283
	CanR/closureL (50/50) 50% M/S sim A, D/4	1	Beverages	154
			Total items	4221
	2
	4

R-Regular can size, L-Large closure, S-Small closure. All groups use the appropriate conversion 3 factors as defined in Table

4

depending upon the group contents.

Table 6 .

 6 High level (low level of detail) groups used in the minimal knowledge models T1, 2

	3	T2 and T3
		Group Description

Table 7 .

 7 Association table for a food group with input data for more than one type of metal

	6
	7	packaging.
	8
				Conversion factor		Extrapolation factor		Market share
	Package	Concentration
	type		group	Min	Best estimate	Max	Min	Best estimate	Max	Min	Best estimate	Max

Table 8

 8 Exposure to a migrant from coated light metal packaging

	Page 29 of 31				Food Additives and Contaminants
	Model	Grouping	Simulant concentration	Surface	Simulant		Exposure			Exposure
				data	area/weight	D	µg/kg actual body weight/day		µg/person/day
					ratio range	reduction
						factor
			D	A, B			Youth	Adult	Senior	Youth	Adult	Senior
	T1	Coarse*	60 µg/kg	0	Not used	Not used 0.16	0.08	0.07	5.72	5.55	4.76
	T2	Coarse*	10 µg/dm²	0	0.08, 6, 19 Not used 0.22	0.11	0.10	7.67	7.68	6.78
	T3	Coarse*	10 µg/dm²	0	0.08, 6, 19 D/X	0.09	0.05	0.06	3.03	3.61	3.73
	T4	Detailed* 10 µg/dm²	0	Actual	Not used 0.17	0.11	0.13	5.74	8.09	8.19
	T5	Detailed* 10 µg/dm²	0	Not used	Not used 0.10	0.06	0.07	3.20	4.17	4.04
	T4-ABD + Detailed* 10 µg/dm²	10 µg/dm²	Actual	Not used 0.56	0.30	0.35	17.17	20.34	23.42
	T4-AB +	Detailed* 0	10 µg/dm²	Actual	Not used 0.52	0.26	0.32	15.12	17.39	20.64
	T4-D +	Detailed* 10 µg/dm²	0	Actual	Not used 0.17	0.11	0.13	5.66	7.96	8.16
	* refer to Tables 5 and 6 for further details
	+ food only -excludes closures, aerosols and tubes

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Table 9

 9 Migration from coated light metal packaging which corresponds to an exposure of 1.5 µg/person/day

					Food Additives and Contaminants
	Model	Grouping	Simulant concentration	Surface	Simulant	Migration µg/dm²	Migration µg/kg
				data	area/weight	D
					ratio range	reduction
						factor
			D	A, B			Youth	Adult	Senior	Youth	Adult	Senior
	T1	Coarse*	60 µg/kg	0	Not used	Not used				15.75	16.23	18.93
	T2	Coarse*	10 µg/dm²	0	0.08, 6, 19 Not used 1.95	1.95	2.21
	T3	Coarse*	10 µg/dm²	0	0.08, 6, 19 D/X	4.95	4.16	4.02
	T4	Detailed* 10 µg/dm²	0	Actual	Not used 2.61	1.85	1.83
	T5	Detailed* 10 µg/dm²	0	Not used	Not used				28.15	21.56	22.30
	T4-ABD + Detailed* 10 µg/dm²	10 µg/dm²	Actual	Not used 0.87	0.74	0.64
	T4-AB +	Detailed* 0	10 µg/dm²	Actual	Not used 0.99	0.86	0.73
	T4-D +	Detailed* 10 µg/dm²	0	Actual	Not used 2.65	1.89	1.84
	* refer to Tables 5 and 6 for further details

+ food only -excludes closures, aerosols and tubes

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