RESEARCH ARTICLE

Compilation of processing factors and evaluation of qualitycontrolled data of food processing studies

Rebekka Scholz1 • Michael Herrmann1• Britta Michalski1

Received: 19 May 2016 / Accepted: 29 July 2016 / Published online: 6 September 2016� The Author(s) 2016. This article is published with open access at Springerlink.com

Abstract Often, agricultural commodities are noteaten raw but undergo processing operations priorto human consumption. These may significantlyaffect the residue levels of pesticides containedtherein and/or thereon. Due to the physico-chemicalproperties of the residue, its concentration maydecrease or increase in processed fractions comparedto the initial concentration in the raw agriculturalcommodity (RAC). The resulting ratio between pro-cessed fraction and RAC is denoted as processingfactor (Pf). Information obtained from processingstudies may serve for 2 different purposes: to decideon compliance of residues in processed products withlegal standards for the RAC, and to refine dietaryexposure estimation of humans and livestock withrespect to residues in processed products. The Ger-man Federal Institute for Risk Assessment (BfR)extracted and compiled the results of several pro-cessing studies, the full reports of which had beenmade available to BfR in the framework of applica-tions either for pesticide authorisation, for the settingof maximum residue levels (MRL), or within the EUactive substances approval programme. EachPf derived from processing studies was reviewedagainst transparent quality criteria and statementshave been made regarding the robustness and

reliability of the study results. Compared to the for-mer version, the revised BfR database includes amore extended, more detailed and more trustworthycompilation of more than 6500 processing factorsaccompanied by relevant information on keyparameters of the underlying processing studies.

Keywords Pesticide residue � Food processing �Processing study � Quality criteria � Processing factor

1 Introduction

Some agricultural commodities are unpalatable intheir raw state or may benefit from processing priorto human consumption. Several publications discussthe impact of such processing operations on the levelof pesticide residues in foodstuff (Holland et al. 1994;Chavarri et al. 2005; Kaushik et al. 2009; Poulsenet al. 2007). Most of the procedures conducted toelucidate the impact of processing operations focuson industrial processing of fruits and vegetables.Much broader information is available from datapackages submitted by pesticide manufacturers forauthorisation of their products. The effect of foodprocessing on residue levels depends on the com-modity as well as the pesticide, and is correlated withindividual physico-chemical properties of the pesti-cide (Burchat et al. 1998). To date, MRLs are set out inAnnexes II or III to Regulation (EC) No 396/2005 onlyfor RACs (European Commission 2005), but apply alsofor processed and/or composite food or feed by con-sidering changes in the levels of pesticide residuescaused by processing and/or mixing (article 20(1)).Similarly, MRLs are established for only a very small

Electronic supplementary material The online version ofthis article (doi:10.1007/s00003-016-1043-3) contains supple-mentary material, which is available to authorized users.

& Rebekka Scholzrebekka.scholz@bfr.bund.de

1 Federal Institute for Risk Assessment, Max-Dohrn-Str.8-10, 10589 Berlin, Germany

J Consum Prot Food Saf (2017) 12:3–14DOI 10.1007/s00003-016-1043-3

Journal of Consumer Protection and Food SafetyJournal fur Verbraucherschutz und Lebensmittelsicherheit

123

number of simply processed commodities by CodexAlimentarius (Codex Alimentarius 2016).

Processing factors are an indispensable tool,mainly for 2 purposes:

1. Providing information to food safety inspectionservices on the scope of changes in residue levelsduring food processing operations, thus, they arecrucial for assessing whether the starting materialhas been in compliance with legal standards.

2. Providing information to risk assessors for refineddietary exposure estimates, such as figures, toallow a more realistic assessment in cases whencommodities are mainly consumed after process-ing. This aspect will become even moreimportant in upcoming cumulative consumerintake assessments.

The aim of the BfR project presented here was togenerate a comprehensive database on quality-con-trolled processing factors. The data compilation isintended to support not only risk assessors in theirevaluation of consumer risks caused by pesticideresidues, but all interested parties in order toimprove the transparency of evaluation results.

2 Existing guidance on how to performprocessing studies

Processing procedures may have a significant impacton pesticide residues, not only related to the mag-nitude of residue concentration (OECD 2008b), butalso to the chemical transformation in (parts of) theparent residue during processing (impact on thenature of residue) (OECD 2007). Several processingoperations have been identified in the OECD Guid-ance ‘‘Document on Overview of Residue ChemistryStudies’’ as being representative of the most widelyused industrial and domestic food processing tech-nologies (OECD 2009). In addition, a largerassortment of processed commodities is published inthe OECD Guidance Document on Magnitude ofPesticide Residues in Processed Commodities (OECD2008a), illustrated by examples of processing typesand recommended extrapolations for typical RACs.To each core procedure and processed matrix, thecorresponding OECD procedure code has beenassigned (Table 1).

In addition to the fractions produced for humanconsumption, by-products are obtained from someprocessing operations that are not discarded but maybe used for livestock feeding. Residues in those

fractions need to be taken into account when pre-dicting the dietary burden of livestock animals andevaluation of the residue transfer into animal com-modities. The Guidance Document on Residues inLivestock (OECD 2013) provides a list of feedstuffsincluding by-products from food processing forhuman consumption. Processing studies thereforeinvestigate processed fractions destined for humanconsumption as well as by-products possibly fed tolivestock.

3 Data sources used to set up the databaseof processing factors

Previous collation work has been done and Pf valueshave been published by BfR; the most recent version3.0 was published in 2011. At that time, mainly pub-lically available data were included, e.g. from

1. The annual Reports of the Joint Meeting onPesticide Residues (JMPR) on the evaluations of

Table 1 OECD procedure codes

OECDcode

Explanation

I Distribution in the edible/non edible portion

II Preparation of fruit juice

III Preparation of canned fruit

IV Preparation of other fruit products

V Preparation of alcoholic beverages (fermentation,distillation)

VI Cooking vegetables, pulses and grains in water(including steaming)

VII Preparation of vegetable juice

VIII Preparation of canned vegetable

IX Miscellaneous preparation of othervegetable products

X Preparation of oil (extraction, pressing, milling in caseof maize) Xa belongs to extraction, Xb belongs topressing, Xc belongs to maize milling

XI Distribution on milling

XII Preparation of sugar

XIII Infusions and extractions

XIV Silage production

XV Processing of products of animal origin includingpreparation of meat and fish (poaching, frying,baking, boiling)

XVI Dehydration

XVII Fermentation of soybeans, rice and others (exceptalcoholic beverages)

XVIII Microwaving vegetable

XIX Pickling

4 R. Scholz et al.

123

pesticide residues in food, published by FAO/WHO,

2. Scientific reports issued by the European FoodSafety Authority (EFSA), encompassing conclu-sions on the peer review of pesticide riskassessments and reasoned opinions on the reviewor modification of existing MRLs.

In addition, data on pulp/peel distribution in citrusfruit were included, which were provided by a foodbusiness operator (Ahlers and Reichert 2007) or col-lected within the framework of the German foodmonitoring programme (BVL 2011). Since the formerversions of the database merely reflected the resultspublished by other scientific bodies, the user was leftwith invalidated figures on processing factors with-out further information. The original study reportshad not been reviewed and no statement whatsoeverwas made, e.g. on the appropriateness of theemployed analytical method or the number of indi-vidual trials.

Hence, the decision was made to completely re-structure the BfR database and factors were derivedonly after carefully scrutinizing the underlyingstudies submitted to BfR in the framework of variouslegal procedures. It is noted that there is some over-lap of the data volumes of studies submitted to BfRand the studies submitted to and evaluated by otherscientific bodies, e.g. EFSA or JMPR.

According to the provisions of the OECD Guide-line 508 (OECD 2008b), processing studies utilisingspiked samples are explicitly referred to as ‘‘notacceptable’’, unless there is experimental evidencethat there is no difference in distribution patterncompared to incurred residues. Based on this,studies involving spiked samples were generallyconsidered not acceptable and were not consideredin the project.

4 Eligibility criteria that need to be addressedby processing studies

Each processing factor used either in risk assess-ment or enforcement of legal standards shouldhave been derived in a study which complies witha minimum of quality criteria, as regulatory deci-sions may largely depend on that piece ofinformation. A set of principle requirements shouldbe fulfilled prior to using such factors in eitherregulatory action of food control inspectors orrefined estimation of dietary exposure. In the fol-lowing, the eligibility criteria employed areoutlined in more detail.

4.1 Representativeness of the employedprocessing procedures

Ideally, the applied experimental setup should mimicrepresentative industrial or domestic standards asclosely as possible (OECD 2008b). However, it isknown that processing conditions are very versatileand a subject to continuous technological progress.Preferably, product properties as defined by foodnorms should be reflected in the processed product.These properties could be related to e.g. minimumfruit content in jam or marmalade, or the standardtypes of flour (e.g. whole meal flour or flour type550).

In view of the importance of industrial products intrade, industrial procedures may be preferred overdomestic scale operations in order to obtain morerepresentative results. Especially fractions destinedfor feeding purposes are only anticipated to beavailable from industrial scale operations.

4.2 Residue definitions

Residue definitions of pesticidal active substancesmay either consist of a single compound (mostlyparent) or of several compounds including relevantmetabolites and degradation products. It is notuncommon that, due to different demands, the resi-due definition for enforcement purposes [simplemarker(s), accessible to routine analysis] deviatesfrom that for risk assessment, which focuses on thetotal toxicological burden.

Residue definitions for monitoring are establishedtogether with MRLs in Reg. (EC) No 396/2005 (Euro-pean Commission 2005) and can be retrieved fromrelevant legislation or the EU Pesticide database (EUPesticide database 2016) maintained by the EuropeanCommission services. No such statutory rules exist forthe definitions for risk assessment purposes.

Furthermore, processing studies should ideallyaddress not only the legally established residue defi-nition but also components of the residue definitionthat are defined for risk assessment. However, defi-nitions applicable for risk assessment are oftensubject to revision. As additional components mightnot have been part of the residue definition when thestudy was designed, the set of analytes might notcomply with the actual residue definition(s) in quite anumber of studies. For these reasons, the BfR datacompilation focuses on the residue definitions formonitoring. In case that a residue definition for riskassessment differs from monitoring, a conversionfactor needs to be considered.

Compilation of processing factors and evaluation of quality controlled data of food… 5

123

4.3 Minimum number of trials

The number of replicate trials within a study is a keyparameter for robustness of the derived processingfactor, particularly when each individual processingfactor is significantly different. Even within the samestudy, processing factors derived from two replicatetrials may show a considerable degree of variability.When individual processing factors from the 2 trialsdiffer by more than 50 % (with a main focus on therelevant processed fraction), OECD Guideline 508(OECD 2008b) recommends to carry out a 3rd trial toenhance consistency of the data and strengthenconfidence in the finally derived factor. In theframework of their mandate to review existing MRLsaccording to article 12 of Reg. (EC) No 396/2005, EFSArequired minimum of 3 trials to ensure sufficientrobustness prior to recommending a processing fac-tor (EFSA 2012, 2014).

4.4 Validity of the analytical method

The analytical method used in the processing studyshould be described in sufficient detail. Parameterslike recovery rates, repeatability, reproducibility andsensitivity should be in line with generally agreedrequirements for analytical methods for pre-regis-tration purposes (SANCO/3029/99) (EuropeanCommission 2000).

The procedural recovery should be within therange of 70–120 %. In addition, the coefficient ofvariation should be below 20 %. If these parameterswere not fulfilled, the study was not consideredacceptable.

4.5 Compliance with standards of goodlaboratory practice

In the area of experimental research, good laboratorypractice (GLP) specifically refers to a quality system ofmanagement controls for research laboratories andorganizations aiming to ensure the uniformity, con-sistency, reliability, reproducibility, quality, andintegrity of chemical safety tests (OECD 1998). Hence,only processing studies prepared in accordance withGLP standards were considered.

4.6 Sample storage conditions

Information on the sample storage conditions andthe time elapsed between sampling and extrac-tion/analysis was considered to be essential to thevalidity of processing studies. The database includes

information about the duration of freezer storage ofthe samples. This information can be related to datafrom storage stability studies of the analyte(s) in therespective matrix type. If the storage conditions werechosen in a way that the duration of proven storagestability was not exceeded, the study was consideredvalid with respect to this criterion.

5 Calculation of Pf

The processing factor is defined as follows:

Pf ¼Residue of processed fraction mg

kg

� �

Residue of RAC mg

kg

� �

Processing factors have been reported afterrounding to 2-digit accuracy. If rounding resultedin a value of 0.00, accuracy has been rounded to 3digits. The range from the lowest to the highest valuehas been reported. If the concentration of the analytein the processed product was below the analyticallimit of quantification (\LOQ), the numerical value ofthe LOQ was used, and the calculated processingfactor was prefixed by the symbol ‘‘\’’. If theconcentration in the RAC was below the LOQ, aremark has been made under ‘‘comments’’ and thestudy was not considered acceptable.

If more than one processing factor is derived fora processed fraction in a study, the median value isused and set out as median Pf. If only 2 processingfactors were reported, no 3rd replicate wasrequired when they did not deviate by more than50 %. This is in line with the present requirements(OECD Guideline 508), but statistical power (e.g.robustness against outliers) is certainly stronglylimited in that cases. If residues in the processedproduct were below the LOQ in all trials, both theindividual and the median Pf figures were prefixedby the symbol ‘‘\’’. A numerical value for themedian Pf was only provided if at least one of theindividual Pf values did not bear the prefix ‘‘\’’.When the residue concentrations in the RAC and inthe processed product were both below the ana-lytical LOQ in all trials, a processing factor was notapplicable.

6 Procedure of creating the database

Following data acquisition, which has been describedabove, assignments and grouping were conducted.

6 R. Scholz et al.

123

At present, BfR is archiving more than 2600 pro-cessing studies, the characteristics of which havebeen listed by active compounds in a Microsoft OfficeExcel worksheet. Table 2 shows a typical screenshotof the database. In general, ‘‘not applicable’’ is indi-cated if no information on the respective criterionwas reported in the study.

6.1 Crops and crop groups

The assignment of the raw agricultural commoditiesused in the processing studies is in accordance withthe crop groupings in Reg. (EU) No 752/2014 (Euro-pean Commission 2014) detailing Annex I to Reg. (EC)No. 396/2005 (European Commission 2005). Thecommodity list employed in Table 3 is an open listand contains all RACs for which processing studieswere available to date.

The uniform classification of crops allows the userto specifically filter the database for the appropriatestudies. For the sake of completeness and conve-nience, the assignment of terms was harmonized inthose cases of unequivocally identical produce withdifferent names. For example, the term rapeseed wasuniformly used instead of canola. And we have cho-sen the British denomination maize (instead of theAmerican term corn). On the other hand, grapeswere divided into red and white varieties in order tocope with the specific technological differences inthe production of red and white wine.

6.2 Matrices and matrix groups

Processed fractions, hereafter called matrices, may benamed differently in different studies. As for RACs itwas important for benefits of consistency to combinethe same products/fractions by a common matrixterm. The entire table of all commodities and relatedmatrices can be retrieved from Annex 1 (supple-mentary data). For example, Table 4 shows thegrouping of the matrices for hops: e.g. the matrix‘‘spent grain’’ coincides with the term ‘‘brewer’sgrain’’. Table 4 also provides information on thenumber of trials in which a respective matrix termwas addressed. Matrices deviating only insignifi-cantly in their processing were consideredsynonymous and combined if no significant differ-ence was anticipated for the processing factors. Forexample, the matrices ‘‘young beer’’, ‘‘cooled beer’’and ‘‘beer’’ were combined in the common matrixgroup ‘‘beer’’.

By this means, the ca. 800 differently named pro-cessed matrices in the complete database (processed

matrix as reported) were consolidated into 175. Thisaggregation improves not only the searchability of aprocessed product but also the comparison of dif-ferent studies. Thus, it enhances the chance for theuser of the database to actually retrieve the completeset of studies matching his or her query.

Another assignment was made for the classifica-tion of flour types (Table 5). Especially for the RACswheat grain and rye grain, various terms werereported in processing studies for flour types.

An overview of the processing procedures evalu-ated within the framework of this project isillustrated graphically in a total of 35 flow charts inAnnex 2 (supplementary data). They describe ideal-ized processes, encompassing all matrix groups of acommodity or of an entire sub-crop group. Forinstance, Fig. 1 shows the idealised flow chart for theprocessing of hops into beer. The processed productsare coloured differently depending on their use asfood or animal feed.

6.3 Comments

The ‘‘comments’’ box provides any further informa-tion that is deemed as relevant for the interpretationof the study, e.g.

1. Additional information on metabolites, enan-tiomers and/or isomers, which are not part of anactual residue definition,

2. Indication of a starting residue concentration inthe RAC below the LOQ,

3. Special processing procedures which do not fallinto any of the categories addressed elsewhere inthe table,

4. Significant deviations from the published analyt-ical method, and

5. Any other deviations/irregularities/remarks.

6.4 Acceptance of a study

It is the final responsibility of the assessor to decideon the acceptability of a processing study and thereliability of the reported results. One of the aims ofthe BfR project was to check all studies based onidentical and particularly transparent criteria. Withno significant discrepancies from generally agreedstandards noted, a study is labelled as ‘‘acceptable’’.If one of the key criteria was not fulfilled, theinformation content of the study was flagged as‘‘indicative’’. With more than one of the keyparameters not addressed adequately, the study wasrendered as ‘‘not acceptable’’ in order to provide

Compilation of processing factors and evaluation of quality controlled data of food… 7

123

Table

2Exce

rptoftheBfR

datab

ase.

Plea

senote

that

thetable

rowsarebeingco

ntinued

onthefollo

wingpag

eprovidingfurther

inform

ationonstudyparam

etersforthe

respec

tive

residuedefi

nition-commodity-matrixco

mbinations.Fo

rea

seofallocationtherowswerenumbered

(1)to

(13)

Line

no.

Residuedefi

nition

Maincrop

group

Subcropgroup

Commodity

Proce

ssed

matrix

consolid

ated

OEC

Dproce

dure

code

Individual

PfMed

ianPf

Number

of

trials

(1)

Ametoctradin

Vegetab

les

Fruiting

vegetab

les

Tomatoes

Puree

VII

0.44–1.15

0.88

4

(2)

Boscalid

Fruits

Berries

andsm

all

fruits

Grapes,red

Pomace,

wet

V2.40–2.60

2.50

2

(3)

Boscalid

Fruits

Berries

andsm

all

fruits

Grapes,red

Must,hea

ted

V0.09–0

.18

0.14

2

(4)

Boscalid

Fruits

Berries

andsm

all

fruits

Grapes,red

Wine,

red

V0.08–0

.12

0.10

2

(5)

Boscalid

Fruits

Pomefruits

Apples

Fruit,washed

IV0.4–1.00

0.65

4

(6)

Boscalid

Fruits

Pomefruits

Apples

Pomace,

wet

II5.8–8

.26.55

4

(7)

Boscalid

Fruits

Pomefruits

Apples

Juice

II0.05–0

.10

0.08

4

(8)

Boscalid

Fruits

Pomefruits

Apples

Puree

II0.70–1.10

0.90

4

(9)

Glyphosate

(incl.trim

esium

aka

sulfo

sate)

Fruits

Citrusfruits

Oranges

Pulp,dried

XVI

[1.20

[1.20

1

(10)

Glyphosate

(incl.trim

esium

aka

sulfo

sate)

Fruits

Citrusfruits

Oranges

Molasses

II[1.40

[1.40

1

(11)

Glyphosate

(incl.trim

esium

aka

sulfo

sate)

Fruits

Citrusfruits

Oranges

Oil

XNot applicab

leNot applicab

le3

(12)

Pico

xystrobin

Cerea

lsBarley

Brewer’sgrain

V[0.50

[0.50

1

(13)

Pico

xystrobin

Cerea

lsBarley

Bee

rV

\0.25–

\0.50

\0.38

2

lineNo.

acce

ptability

ofstudy

GLP

storage

conditions

analytical

method

proce

dural

reco

very

further

commen

tsreference

EFSA

reference

(1)

Yes

Yes

Storedat

-18

�CBASF

method

no.L0

078

91%,SD

14,CV

15%

Metab

olite(7-amino-5-

ethyl[1,2,4]triazolo[1,5-

a]pyrim

idine-6-y-l)acetic

acid)an

dmetab

olite(7-

amino-5-

ethyl[1,2,4]triazolo[1,5-

a]pyrim

idine-6-carboxylic

acid)areincluded

;Pf

derived

from

sum

of

paren

tco

mpoundan

dmetab

olites

[58]

EFSA

Journal

2012;10(6):2771

(2)

Yes

Yes

Stored‘‘frozen’’less

than

9month

BASF

method

no.445/0

87.7%,SD

4.0,

CV4.6

%[1]

EFSA

Journal

2014;12(7):379

9

(3)

Yes

Yes

Stored‘‘frozen’’less

than

9month

BASF

method

no.445/0

87.7%,SD

4.0,

CV4.6

%Mashhea

tedto

approx.

60�C

[1]

EFSA

Journal

2014;12(7):379

9

8 R. Scholz et al.

123

Table

2co

ntinued

lineNo.

acce

ptability

ofstudy

GLP

storage

conditions

analytical

method

proce

dural

reco

very

further

commen

tsreference

EFSA

reference

(4)

Yes

Yes

Stored‘‘frozen’’less

than

9month

BASF

method

no.445/0

87.7%,SD

4.0,

CV4.6

%[1]

EFSA

Journal

2014;12(7):379

9

(5)

Yes

Yes

Storedat

-18

�Cfor5months

BASF

method

no.445/0

92.1%,SD

10.9,

CV11.8

%[16]

EFSA

Journal

2014;12(7):379

9

(6)

Yes

Yes

Storedat

-18

�Cfor5months

BASF

method

no.445/0

92.1%,SD

10.9,

CV11.8

%[16]

EFSA

Journal

2014;12(7):379

9

(7)

Yes

Yes

Storedat

-18

�Cfor5months

BASF

method

no.445/0

92.1%,SD

10.9,

CV11.8

%[16]

EFSA

Journal

2014;12(7):379

9

(8)

Yes

Yes

Storedat

-18

�Cfor5months

BASF

method

no.445/0

92.1%,SD

10.9,

CV11.8

%[16]

EFSA

Journal

2014;12(7):379

9

(9)

No

No

Storedfor

22months

GLC-FPD

74%

Activemetab

olite

(aminomethylphosphonic

acid)reported

;RA

C\

LOQ

[716]

notap

plicab

le

(10)

No

No

Storedfor

22months

GLC-FPD

74%

Activemetab

olite

(aminomethylphosphonic

acid)reported

;RA

C\

LOQ

[716]

notap

plicab

le

(11)

No

No

Storedfor

22months

GLC-FPD

74%

Activemetab

olite

(aminomethylphosphonic

acid)reported

;RA

C\

LOQ

[716]

notap

plicab

le

(12)

No

Yes

Storedfrozenfor

10months

SOPRA

M28

8/01

93%,CV3.04%

RAC\

LOQ

[991]

EFSA

Journal

2011;9(12):2488

(13)

Yes

Yes

Storedfrozenfor

10months

SOPRA

M28

8/01

93%,CV3.04%

[991]

EFSA

Journal

2011;9(12):2488

Compilation of processing factors and evaluation of quality controlled data of food… 9

123

reliable Pf information. It is explicitly emphasizedthat this categorization scheme is that of the creatorof the database. Depending on the background ofhis or her own experience and specific needs, theuser of the data base may come to a divergingconclusion.

6.5 References and bibliographic information

For the identification of the underlying processingstudies, full bibliographic information has beengiven, such as title of the study, authors(s) and year ofpublishing. If there was a Reasoned Opinion availableby EFSA on the review of the existing MRLs for theactive substance according to Article 12 of Reg. (EC)No 396/2005 (European Commission 2005), this isadditionally referenced. However, due to lack ofdetails from the reports, normally it cannot bereproduced which particular processing studies wereunderlying the processing factors recommended bythe EFSA. The resulting processing factors maytherefore differ between EFSA’s Reasoned Opinionand the BfR database for the same pesticide/com-modity/processing procedure combination.

7 Results and discussion

More than 2600 processing studies on 193 activesubstances have been reviewed in the project. Suchstudies are normally data-protected and not publiclyaccessible. Earlier versions of the BfR database andother projects like a compilation run by the NationalInstitute for Health and Environment (RIVM) in theThe Netherlands (RIVM, 2015) suffer from onlyreproducing results of evaluation studies done byother scientific bodies like EFSA or JMPR. In contrast,the new BfR processing factors database reflects theoutcome of an exercise in which each individualprocessing study was thoroughly scrutinized underaspects of acceptability criteria for a set of keyparameters governing the reliability of the study

Table 3 Group assignment of crops/commodities

Main crop group Sub crop group Commodity

Fruits Citrus fruits Grapefruit

Lemons

Limes

Mandarins

Oranges

Pome fruits Apples

Pears

Stone fruits Apricots

Cherries

Peaches

Plums

Berries and small fruits Grapes, red

Grapes, white

Black currants

Strawberries

Vegetables Root and tubervegetables

Potatoes

Carrots

Bulb vegetables Onions

Fruiting vegetables Tomatoes

Chili peppers

Sweet peppers

Gherkins

Melons

Pumpkins

Brassica vegetables Head cabbage

Savoy cabbage

Leaf vegetables, herbsand edible flowers

Lettuce

Spinach

Mint

Legume vegetables Beans

Peas

Fungi, mosses andlichens

Mushroom

Oilseedsand Oilfruits

Oil seeds Linseed

Peanut

Sunflower seed

Rapeseed

Soya bean

Cotton seed

Oil fruits Olive

Cereals Barley

Maize

Oats

Rice

Rye

Sorghum

Wheat

Table 3 continued

Main crop group Sub crop group Commodity

Teas, coffee, herbalinfusions andcocoa

Teas Camellia sinensis

Coffee beans

Hops Hops

Sugar plants Sugar beet

Sugar cane

10 R. Scholz et al.

123

results. The outcome has been reported in the data-base on a single study basis. In order to build thedesired degree of confidence in the derived process-ing factors, a number of critical parameters wereverified. The information extracted from the corre-sponding study reports on each quality criterion canbe retrieved from the database. This enables the useof the information according to specific needs. Atotal of 6500 processing factors were reported in thestudies, out of which circa 1100 could not be repro-duced because the residues in the processed matrixand in the RAC were lower than LOQ. For reasons ofcompleteness, they were, however, not omitted.About 2800 processing factors reached the minimumquality requirements and the derived processing

factors have been tagged as ‘‘acceptable’’. 17 % of theprocessing factors recorded in the database wereflagged as ‘‘not acceptable’’, because more than onecritical parameter was not met, and 40 % were flag-ged as ‘‘indicative’’ due to one parameter not havingbeen met.

The experience gained from the comprehensivereview of the large number of studies allows for somecritical remarks on the general design of processingstudies and the processing procedures describedtherein. In particular, the following striking aspectsare highlighted for further improvements.

The OECD guidance does not specify or prescribeany details of the processing technique(s) that shouldbe simulated in studies. This deliberate flexibility is toleave room for the broad range of different types ofprocessing techniques, ranging from industrial scalefood producers continually improving their practiceon one end, to artisan food or domestic produce atthe other end. Such limited specification of processesleaves the regulatory assessor with a difficult decisionon the representativeness of a single study fromwhich a processing factor is taken. Furthermore,information is frequently lacking on the actual rangeof factors for a processed produce which may beencountered in practice due to diverging processingtechnologies. A typical example for this is the pro-duction of beer. Meanwhile, about 30–35 % of thebeers are produced from hop extracts, a procedure

Table 4 Matrix grouping forthe processed fractionsresulting from hops in beerbrewing

Commodity Processed matrixas reported

Processed matrixconsolidated

Numberof trials

Hops Green cones Cones 17

Dried cones Cones, dried 75

Malt Malt 3

Brewer’s malt Malt 8

Extracted hops Hops, extracted 3

Wort Wort 1

Wort after filtration Wort, filtrated 4

Wort cooked Wort, cooked 4

Young beer Beer 5

Beer Beer 92

Beer, cooled Beer 8

Brewer‘s grain Brewer‘s grain 21

Spent grain Brewer’s grain 1

Yeast Yeast 2

Brewer’s yeast Brewer’s yeast 16

Spent yeast Brewer’s yeast 4

Lees Hops draff 2

Hops draff Hops draff 18

Spent hops Hops draff 13

Table 5 Classification of flour types

Commodity Flour types

Wheat Type 140 Low grade flour (feeding)

Type 405 Patent flour

Type 550 White flour

Type 812 High gluten flour

Type 1050 Brown flour

Type 1600 Whole meal flour

Rye Type 815 Light rye flour

Type 997 Rye flour

Type 1050 Heavy rye flour

Compilation of processing factors and evaluation of quality controlled data of food… 11

123

not reflected by the majority of the available studiesinvolving the use of dried hop cones (or hop pellets).Likewise, there have been numerous developmentsconcerning the preservation of food. In many cases, astatement regarding the extent to which the simu-lated processing operation in the lab actually mimicsrecent developments in the food processing industrywould be helpful, as well as a comparison of theapplied technology to competing technologies.

Another source of confusion and erroneous inter-pretation of processing factors is a non-standardizeddesignation of processed fractions. In the evaluatedstudies, more than 800 differently named processedfractions were registered. For benefits of consistency,it was deemed prudent to combine the more or lessidentical (but differently named) products/fractionsinto 175 consolidated terms for processed matrices.This significantly improves the ability to retrieve thecomplete information from the database, but is alsofor ease of comparing results of studies using deviantterminologies. One experience gained in the projectis that harmonisation and amplification of the cur-rent classification/denomination of processedmatrices are highly desirable—preferably associatedby a coding system for processing operations andprocessed fractions.

Some of the study reports suffer severely from thelack of information on important parameters, e.g.duration and temperature of heating steps, whichwould substantially facilitate the affiliation of thestudy outcome. In the absence of such information,judgement on the representativeness of the proce-dure is difficult and intercomparison with resultsfrom other studies is impeded. Similarly, productshave been characterized sparsely and/or in a verygeneral manner in some of the study reports, forexample, whether the end product was double ortriple concentrated tomato paste.

Another striking obstacle preventing the deriva-tion of processing factors in some studies is thatexperiments employed a starting material (RAC) withresidues below the LOQ of the analytical method.Even in case of an expected accumulation in pro-cessed fractions (Pf[ 1) such studies are notsuitable to provide processing factors in a quantita-tive manner, hence rendering the study resultsobsolete.

Finally, it is considered worthwhile to furtherexplore possibilities of extrapolation of study resultsto similar commodities/processes. The GuidanceDocument on magnitude of pesticide residues inprocessed commodities (OECD 2008a) indicates that

Fig. 1 Flow chart of the processing of hops into beer

12 R. Scholz et al.

123

for commodities of the same commodity groupundergoing the same processing procedure; theresults obtained for one commodity can be extrapo-lated to the other similarly processed commoditieswithin this group. These recommendations are basi-cally confirmed by the studies recorded in the BfRdatabase. For example, the results from processingoranges into orange juice may be extrapolated toother citrus fruits. Nevertheless, even this apparentlystrikingly clear rule should be cautiously applied witha closer scrutiny of the processed fraction. Forexample, rather divergent factors were found in jui-ces originating from pome fruit, which on a closerlook were due to different processing proceduresyielding either clear or turbid juice.

With a view to the large number of processedproducts, an extension of the existing rules forextrapolation should be explored. However, any newextrapolation has to be based on at least a minimumnumber of side-by-side processing studies. In thepast, processing studies were almost exclusivelyconducted on a very limited number of representa-tive crops. This does not give leeway forsubstantiating new extrapolations to other RACswhich are important in trade or make up a signifi-cant share of consumer group diets.

Likewise, it might be worthwhile to explore pos-sibilities of processing factors being extrapolatedfrom one substance to another, given that those areclosely rated in terms of structure and/or physico-chemical properties.

8 Conclusion

Processing factors are valuable tools both for con-cluding on whether processed food or feed wasproduced in compliance with legal standards and forrefining dietary exposure assessments. The revisedBfR database offers a detailed compilation of suchprocessing factors. Quality information on keyparameters of the processing studies allows for ratingof robustness and reliability of the results. Thus, theBfR database may be considered a milestone in pro-viding a scientific background for establishing AnnexVI to Regulation (EC) No 396/2005. To further developthe collected information towards a commoninstrument for regulatory decision making across theEU, a close cooperation is scheduled with partners ofother European institutions. Furthermore, some rec-ommendations concerning the set-up andinterpretation of processing studies might find theirway into existing international guidance.

Compliance with ethical standards

Conflict of interest The authors declare that they have noconflict of interest.

Open Access This article is distributed under the terms of theCreative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permitsunrestricted use, distribution, and reproduction in any med-ium, provided you give appropriate credit to the originalauthor(s) and the source, provide a link to the Creative Com-mons license, and indicate if changes were made.

References

Ahlers W, Reichert T (2007) Oberflachen-Konservierungsstoffeund Akute Referenzdosis—Ergebnisse einer Testreihe beiZitrusfruchten, Kooperation des lebensmittelchemischenUntersuchungsrings des Landesverbands Baden-Wurttem-berg des Fruchte-Import- und -Großhandels e.V. und derAtlanta AG (actually: Univeg Deutschland GmbH)

BfR (2016) http://www.bfr.bund.de. Accessed 1 July 2016Burchat CS, Ripley BD, Leishman PD, Ritcey GM, Kakuda Y,

Stephenson GR (1998) The distribution of nine pesticidesbetween the juice and pulp of carrots and tomatoes afterhome processing. Food Addit Contam 15:61–71. doi:10.1080/02652039809374599

BVL (2011) Berichte zur Lebensmittelsicherheit 2011, Monitor-ing. http://www.bvl.bund.de/SharedDocs/Downloads/01_Lebensmittel/01_lm_mon_dokumente/01_Monitoring_Berichte/archiv/lmm_bericht_2011.pdf?__blob=publicationFile&v=4. Accessed 26 July 2016

Chavarri MJ, Herrera A, Arino A (2005) The decrease inpesticides in fruit and vegetables during commercialprocessing. Int J Food Sci Technol 40:205–211. doi:10.1111/j.1365-2621.2004.00932.x

Codex Alimentarius (2016) Codex pesticides residues in foodonline database. http://www.fao.org/fao-who-codexalimentarius/standards/pesticide-mrls/en/. Accessed 28 February2016

EU Pesticide database (2016). http://ec.europa.eu/food/plant/pesticides/eu-pesticides-database/public/?event=homepage&language=EN. Accessed 28 Feb 2016

EFSA (2012) Reasoned opinion on the review of the existingmaximum residue levels (MRLs) for fosetyl according toArticle 12 of Regulation (EC) No 396/2005. http://www.efsa.europa.eu/sites/default/files/scientific_output/files/main_documents/2961.pdf. Accessed 23 March 2016

EFSA (2014) Reasoned opinion on the review of the existingmaximum residue levels (MRLs) for thiabendazole accord-ing to Article 12 of Regulation (EC) No 396/2005. http://www.efsa.europa.eu/sites/default/files/scientific_output/files/main_documents/3750.pdf. Accessed 23 March 2016

ENV/JM/MONO(2013)8 (2013). http://www.oecd.org/env/ehs/pesticides-biocides/publicationsonpesticideresidues.htm.Accessed 28 Feb 2016

European Commission (1997) Guidelines for the generation ofdata concerning residues as provided in Annex II part A,section 6 and Annex III, part A, section 8 of Directive91/414/EEC concerning the placing of plant protectionproducts on the market, Appendix E—Processing Studies,7035/VI/95-rev.5. http://ec.europa.eu/food/plant/pesticides/guidance_documents/docs/app-e.pdf. Accessed 28 Feb2016

Compilation of processing factors and evaluation of quality controlled data of food… 13

123

European Commission (2000) Residues: Guidance for generat-ing and reporting methods of analysis in support of pre-registration data requirements for Annex II (part A,Section 4) and Annex III (part A, Section 5) of Directive91/414. SANCO/3029/99 rev. 4. http://ec.europa.eu/food/plant/pesticides/guidance_documents/docs/wrkdoc12_en.pdf. Accessed 23 March 2016

European Commission (2005) Commission Regulation (EC) No396/2005 on maximum residue levels of pesticides in or onfood and feed of plant and animal origin and amendingCouncil Directive 91/414/EEC (OJ L 70/1, 16.3.2005)

European Commission (2009) Commission Regulation (EU) No1107/2009 concerning the placing of plant protectionproducts on the market and repealing Council Directives(OJ L 903/24, 3.11.2009)

European Commission (2013) Commission Regulation (EC) No283/2013 setting out the data requirements for activesubstances, in accordance with Regulation (EC) No.1107/2009 of the European Parliament and of the Councilconcerning the placing of plant protection products onthe market (OJ L 93/1, 3.4.2013)

European Commission (2014) Commission Regulation (EU) No752/2014 replacing Annex I to Regulation (EC) No.396/2005 of the European Parliament and of the Council(OJ L 208/1, 15.07.2014)

Holland PT, Hamilton D, Ohlin B, Skidmore MW (1994) Effectsof storage and processing on pesticide residues in plantproducts. Pure Appl Chem 66:335–356

Kaushik G, Satya S, Naik SN (2009) Food processing a tool topesticide residue dissipation—A review. Food Res Int42:26–40. doi:10.1016/j.foodres.2008.09.009

OECD (1998) OECD Series on Principles of Good LaboratoryPractice and Compliance Monitoring, Number 1; ENV/MC/

CHEM(98)17. http://www.oecd.org/env/ehs/testing/oecdseriesonprinciplesofgoodlaboratorypracticeglpandcompliancemonitoring.htm. Accessed 28 Feb 2016

OECD (2007) Test Guideline No. 507: Nature of the PesticideResidues in Processed Commodities—High TemperatureHydrolysis, OECD Guidelines for the Testing of Chemicals,Section 5, OECD Publishing. doi:10.1787/9789264067431-en

OECD (2008a) OECD Guidance Document on the Magnitude ofPesticide Residues in Processed Commodities ENV/JMMONO(2008)23. http://www.oecd.org/env/ehs/pesticides-biocides/publicationsonpesticideresidues.htm. Accessed 28February 2016

OECD (2008b) Test Guideline No. 508: Magnitude of thePesticide Residues in Processed Commodities, OECDGuidelines for the Testing of Chemicals, Section 5, OECDPublishing. doi:10.1787/9789264067622-en

OECD (2009) OECD Guidance Document on Overview ofResidue Chemistry Studies; Series on Pesticides, No. 32;Series on Testing and Assessment, No. 64; ENV/JM/MONO(2009)31. http://www.oecd.org/env/ehs/pesticides-biocides/publicationsonpesticideresidues.htm. Accessed 28Feb 2016

OECD (2013) OECD Guidance Document on Residues inLivestock; Series on Pesticides, No. 73

Poulsen ME, Hansen HK, Sloth JJ, Christensen HB, Andersen JH(2007) Survey of pesticide residues in table grapes: deter-mination of processing factors, intake and risk assessment.Food Addit Contam 24:886–895. doi:10.1080/02652030701245320

RIVM (2015) List of processing factors to evaluate pesticideresidues measured in The Netherlands. https://acceptatie.chemkap.rivm.nl/en/Topics/C/ChemKAP/Fruit_and_Vegetables/Processing_factors. Accessed 23 June 2016

14 R. Scholz et al.

123