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Residues on food items for birds and mammal
Robert Luttik, National Institute for Public Health and the Environment, NLValencia workshop 2007
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History: Nomograms of Kenaga
The EPA food-chain (Kenaga) nomogram used to predict maximum pesticide residues in ppm following application to different categories of plants and plant parts
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History: Nomograms of Kenaga
Premises are that the residues that one can expect after spraying are not the result of the compound but of the crop and that the initial concentration increases proportional with increasing dose.
In 1973 Kenaga proposed, for lack of measurements, to use the residue data of forage crops and cereals for small and large insects, respectively.
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History: European equivalent
6.3 * D1.3 * DFruit
8.9 * D2.7 * D Cereals / large insects
11 * D2.7 * DPods
52 * D29 * DSmall seeds / forage crops/small insects
112 * D31 * D Leaves and leafy crops
98 * D 82 * DLong grass
214 * D112 * DShort grass
Maximum valuesTypical valuesPlant/plant parts
Relationship between "typical" and maximum residue concentrations on plants or parts of plants (in mg/kg fresh weight) and the dosage (D) of plant protection products (in kg active ingredient per hectare) immediately after spraying.
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History: Guidance document 2002
115.1Large insects
5229Small insects
114.8Fruit/pods/large seeds
8740.2Leaves/leafy crops/forage crops/small seeds
6932.1Long grass
14275.7Short grass
RUD 90th
percentile
RUD Arithmetic
meanFood type
Residue unit doses to be used according to the Guidance documentfor birds and mammals (2002) after Fletcher et al. (1994).
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History: Guidance document 2002
Note in guidance document:
The residue estimate for small insects appears unsatisfactory, and as soon as better information becomes available this surrogate should be replaced.
Research is highly desirable to develop more robust data for residues in insects, also with regard to the temporal pattern.
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Revision of guidance document
•Residues on insectsBoth PSD and ECPA have funded much work in this area.PSD funded work has focused on working from the lab to the fieldand has concentrated on issues such as what invertebrates birds eatThe industry approach has been to develop a generic protocol and produced many field based data.
•Residues on vegetationThe existing dataset has been recently reviewed by Canada (Baril et al. 2005)
•MAF and TWAprobably we will provide tables for MAF and a TWA calculator (excel)
•Guidance on how to carry out residue trialsWe will produce a guidance document including to decide on howmuch data are needed before the default values can be replaced. How to deal with studies on degradation time.
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Revision of guidance document
All following presented data are still under debate.
No decision has been made what to propose for the guidance document.
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Insects: ECPA / industry data set
Analysis of field arthropod residue studies from different ECPA companies by RIFCON GmbH to extract suitable initial maximum residue levels
=> Initial residues measured as highest value within 7 days after application (worst-case)
=> Residues per unit doses (RUD)
• Consideration of different substance classes / application and sampling techniques etc. according to a questionnaire provided by industry.
• Consideration of available data from the literature and other sources.
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Insects: ECPA / industry data set
Field studies conducted following GAP and standard agricultural practice
22 Studies (91% GLP) representing 25 different crop / pesticide scenarios from North America and Europe
67 datasets which differ in:study location, active ingredient, crop, method of arthropod sampling.
Database:
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Insects: ECPA / industry data set
ScenariosScenarios coveredcovered
⇒ 16 different active ingredients from 13 different chemical classes made up the dataset. insecticides (n=10), fungicides (n=4) or herbicides (n=2)
⇒ Data were grouped within each of the major crop types (cereals, leafy crops/vegetables and orchards/vines)
-2Grasslandlate / post-harvest4CerealsBare soil / early / late11Miscellaneous Vegetables*early / late6Potatoesearly / late7Cottonduring or after flowering6Vineduring or after flowering31Orchards
Growth stage during application
No of trials (or data sets)Crop types
* Miscellaneous vegetables contain alfalfa, peas, French beans, lentil, endive etc.
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Insects: ECPA / industry data set
ArthropodArthropod categoriescategories and and samplingsampling methodsmethods
-car netting, light traps and malaise trapsFlying arthropods
-mainly inventory spray and beating method -collected arthropods (sweep nets)-exposure methods of larvae and adults at foliage level
Foliage dwelling arthropods
-mainly pitfall traps-collected arthropods (aspirators, by hand)-crickets placed in exposure chambers at soil level
Ground dwelling arthropods
Sampling techniquesArthropod class
Arthropods were classified as ground dwelling, foliage dwelling and flying arthropods according to sampling technique
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– flying insects (6 data sets)
• car netting, light traps
– leaf dwelling arthropods (23 data sets)
• inventory spray, beating on vegetation
– ground dwelling arthropods (37 data sets)
• pitfall traps
Arthropod Sampling and Arthropod Sampling and ForagingForaging StrataStrata
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Summary of Insect RUD valuesSummary of Insect RUD values
47.89.5all pesticides all crops
Leaf dwellersfoliage application
15.66.7herbicides (orchards/vines), all pesticides early growth stages of leafy crops
Ground dwellersground application
9.8*3.6*insecticides and fungicides: orchards/vines, late growth stages of leafy crops
Ground dwellersfoliage application
6.61.4all pesticides all crops
Flying insects90%tileMedianPesticide and CorpArthropods
RUD [mg/(kg*h)]
* value for fungicides (covering insecticides)
Preliminary results
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ECPA / industry data set
RUD current SANCO vs. experimental residue data from ECPA database
Difficult use of RUD for small and large arthropods (as recommended by current SANCO/4145) for refined risk assessments because no clear definition of what is ‘small’ and ‘large’
A differentiation into ecological groups (e.g. foliage vs. ground dwelling arthropods) is more appropriate instead of arbitrary and undefined size classes (e.g. small vs. large).
The default values (52 / 29 mg/kg small insects) from the guidance document (SANCO/4145/2000) appear to overestimate actual arthropod residues.
Proposed RUD values for ecological categories of arthropods fromthe ECPA database can be updated as new data become available
Summary Results and ConclusionsSummary Results and Conclusions
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Residues on insects –PSD study
• Extended lab studies for cereal and broad-leafed crops
• Pot grown plants (cereal, cabbage, beans) infested with invertebrates (aphids, syrphids, caterpillar identified as major food items for birds and mammals) and oversprayedusing boom sprayer with pesticides
• Range of 9 pesticides- insecticides, herbicides, fungicides with range of formulations
• Samples taken immediately after drying
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Residues on insects – PSD study
3837(0-48)
18(0-47.8)
27(0-57)
109(0-186)
Overall 90th
percentile (range)
4.613(0-35)
3.4(0-8.5)
11(0-40)
31(0.008-150)
Overall mean
(range)
MeanPierisbrassicae
on cabbage
Episyrphus
balteatus
on cereal
Acyrthosiphon pisum
on bean
Rhopalosiphumpadi
on cereal
RUD
Preliminary results
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Residues on insects – PSD study
• Plot studies• Cereal and cabbage grown on plots• Infested with aphids and Pieris brassicae larvae
(as highest residues in extended lab studies)• Oversprayed with boom sprayer with prochloraz,
chlorpyrifos, tebuconazole and L-cyhalothrin• Samples taken when dry• Beetles placed in plots and oversprayed
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Residues on insects – PSD study
8747226155Overall
88532391970.01L-cyhalothrin
62352021550.25Tebuconazole
153782131870.9Chlorpyrifos
3122103810.4Prochloraz
Pierisbrassicae
90th
Pierisbrassicae
Mean
Rhopalosiphumpadi
90th
Rhopalosiphumpadi
mean
Rate (kg ai/ha)
Pesticide
Preliminary results
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Residues on insects – PSD study
1514(1.4-17)
28(1.9-134)
15(1.5-29)
90th percentile (range)
9.04.9(1.1-13)
16 (1.3-56)
6.0(1.0-19)
Mean (range)
All beetlesBeetleCereal
Beetlecabbage
Beetlebare soil
Preliminary results
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Residues on vegetationNew research available:
Baril, Whiteside and Boutin (2005) ETC 24: 360-371
Database contains 1488 residue values originating from 314 sources
From literature but also 25 field studies submitted by manufacturers in support of registration.
Much larger database compared to Fletcher et al (1994), which was already much larger than the database of Kenaga.
Still under discussion within the working group whether the values given in the paper are representative for the European agricultural practice.
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Residues on vegetation
57423523101671916Pods1035813118212515Grains128474125101893419Large fruits
14127434234Small fruits
99th 95th 90th 75th50thnstdmean
RUDS on fruits
and seeds
Small fruits are berries and small fruits from orchards (apricot, cherry, plum, etc.)
Large fruits are fruit from orchards like apples, tomato, eggplant and gourds.
Pods are pulse crops and okra.
Categories proposed by authors
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Residues on vegetation
1951863333
9
n
BBBBA
AB
sign.
135Tomato1920Large fruits from orchards
3419Gourds229Eggplant
333Small fruits from orchards
86Berries
stdmeanRUDS on fruits
Other possibilities for food categories
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Residues on vegetation
876543424Thin plants
183140674922654337Tall grasses
388165121642633317261Vegetable row crops
2021801526725275951Oilseeds
2071601167236345056Short plants
22059493381255090403170Orchard/vineyard
69738418910760309153100Field crops
21519516311684595490Shrubs
99th 95th 90th 75th 50th nSTDmeanRUDs on leaves
Field crops: cereals, forage grasses, forages legumes and turf
Categories proposed by authors
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Residues on vegetation
significanceUnderlying cropsBaril et al choice
Pulse crops
Large whorled leaves
Medium-sized plants
Woody vines
Fruit trees
Turf
Forages legumes
Forage grasses
Cereals
CD
CD
ABCD
ABC
ABC
ABCD
Thin plants
Tall grasses
Vegetable row crops
Oilseeds
Short plants
Orchard/vineyard
Field crops
Shrubs
E
D
BCD
ABCD
ABCD
ABCD
AB
A
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Residues on vegetation
9650.640.2Fletcher values for leaves
21947.862.7Small plants
2759.451.2ABCDOilseeds
3449.856ABCDShort leafy plants
902956.6ABCForage legumes
3768.677.8ABCDForage grasses
3142.879.4ABCTurf
nstdmean“leaf type”
Other possible choices that can be made
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MAF and TWA
MAF = Multiple Application FactorReplaces a series of individual applications by one virtual ‘total application’.Underlying assumption: single 1st order degradation kinetics (SFO)acute scenario:specific calculation to achieve 90th percentile (or other percentile)long-term scenario:based on standard equation for SFOc = c0 × exp(-k × t) with k = ln(2)/DT50
TWA = time-weighted averageReplaces a non-static concentration curve by a constantUnderlying assumption: single 1st order degradation kinetics (SFO)acute scenario:not applicablelong-term scenario:based on standard equation for SFOctwa = c0 × (1 - exp(-k × t))/(k × t) with k = ln(2)/DT50
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0
0,25
0,5
0,75
1
1,25
1,5
1,75
2
0 5 10 15 20 25 30 35
time
conc
entr
atio
nMAF and TWA
working example:
3 applicationsinterval 7 d
DT50 = 7 d
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MAF and TWA
0
0,25
0,5
0,75
1
1,25
1,5
1,75
2
0 5 10 15 20 25 30 35
time
conc
entr
atio
n
MAFtransforms 3 singleapplications into onevirtual ‘total application’here: MAF = 1.75
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0
0,25
0,5
0,75
1
1,25
1,5
1,75
2
0 5 10 15 20 25 30 35
time
conc
entr
atio
nMAF and TWA
twareplaces a non-staticconcentration curveby a constanthere: ftwa = 0.736
areas match
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0
0,25
0,5
0,75
1
1,25
1,5
1,75
2
0 5 10 15 20 25 30 35
time
conc
entr
atio
nMAF and TWA
MAF × twastepwise calculationfor multiple applicationshere: MAF × ftwa = 1.022
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0
0,25
0,5
0,75
1
1,25
1,5
1,75
2
0 5 10 15 20 25 30 35
time
conc
entr
atio
nMAF and TWA
MAF × twaselection of appropriatetime window
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a MAF can bederived
read outMAF × twa
here
selection ofinput parameters
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Future use of degradation kineticscalculations to be based on single 1st order kinetics (SFO)volatilisation, wash-off or photolysis of residues might result in non-SFO best fit kinetics, but use of SFO ensures conservative approach for the relevant time intervals shortly after application
Future use of MAFgives maximum concentration to be expected for acute exposure scenarionew GD will include equations to calculate 90th percentile MAF (or other percentile when appropriate)no longer to be used alone for long-term exposure scenario
Future use of ftwa
to be used in long-term exposure scenario as a combined factorMAF × ftwacalculation using a moving time-windowcheck applicability of averaging for certain endpoints first
MAF and TWA
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Guidance for field experiments
• It is intended to provide methodological recommendations how to perform arthropod residue studies under field conditions, considering:– Study site selection, plot size, replicates– Sampling methods for different strata (foliage, ground
dwellers etc.)– Sample size and frequency (for determination of residue
decline data)• Recommendations may be provided as an annex /
supplement to the new GD
Will this be helpful for authorities (study interpretation) and notifiers / CRO‘s (study performance)?
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