Pesticideresiduesinconventional,integratedpest …integratedpest...

Pesticide residues in conventional, integrated pestmanagement (IPM)-grown and organic foods: insightsfrom three US data sets

B. P. Bakery, C. M. Benbrook‡, E. Groth III}* andK. Lutz Benbrook‡y Organic Materials Review Institute, PO Box 11558. Eugene, OR97440, USA; ‡ Benbrook Consulting Services, 5085 Upper PackRiver Road, Sandpoint, ID 83864, USA; } Consumers Union ofUnited States, Inc., 101 Truman Avenue, Yonkers, NY 10703-1057 ,USA

(Received 22 August 2001; revised 26 October 2001; accepted30 October 2001)

An analysis of pesticide residue data was performed todescribe and quantify diŒerences between organicallygrown and non-organic fresh fruits and vegetables.Data on residues in foods from three diŒerent marketcategories (conventionall y grown, integrated pest man-agement (IPM)-grown/no detectable residues (NDR),and organically grown) were compared using data fromthree test programmes: The Pesticide Data Program ofthe US Department of Agriculture; the MarketplaceSurveillance Program of the California Department ofPesticide Regulation; and private tests by theConsumers Union, an independent testing organization.Organically grown foods consistently had about one-third as many residues as conventionally grown foods,and about one-half as many residues as found in IPM/NDR samples. Conventionally grown and IPM/NDRsamples were also far more likely to contain multiplepesticide residues than were organically grown samples.Comparison of speci®c residues on speci®c crops foundthat residue concentrations in organic samples wereconsistently lower than in the other two categories,across all three data sets. The IPM/NDR category,based on data from two of the test programmes, hadresidues higher than those in organic samples but lowerthan those in conventionally grown foods.

Keywords : pesticide residues, organic foods, inte-grated pest management-grown foods, contaminants

Introduction

Reducing dietary exposure to pesticidesÐparticularlyin infants’ and children’s foodsÐis a major risk-management goal of government regulatory agencies,the food industries and the agricultural community,and many consumers prefer to buy foods with re-duced residues (Hartman 1996, US EPA 1996). In theUSA, passage of the Food Quality Protection Act(FQPA) in 1996 gave the Environmental ProtectionAgency (EPA) a mandate to review and strengthensafety limits for pesticide residues in foods. Recentand expected regulatory actions will restrict or phaseout high-risk uses of and establish lower safe exposurelevels for many pesticides (US EPA 2000a±c, Grothet al. 2001), which in turn will further stimulateinterest in agricultural practices that can help achievelowered exposure limits. In that context, quantitativemeasures of the eŒects of current production practiceson residues should be widely useful.

Organic farming, which prohibits most synthetic pes-ticides and restricts the use of permitted naturalpesticides, appears to oŒer foods essentially free ofpesticide residues, and consumers perceive organicfoods to be a lower-residue choice (Hartman 1996).In recent years, a new market sector consisting ofproduce marketed as produced with integrated pestmanagement (IPM grown) and foods certi®ed ascontaining `no detectable residues’ (NDR) has arisen,and currently competes with the organic category as alower-residue alternative to conventionally grownfruits and vegetables.

However, few independent scienti®c studies havedirectly compared residues in these three marketcategories of foods. In part because of this lack ofpublished data, public debate of this issue has been

Food Additives and Contaminants , 2002, Vol. 19, No. 5, 427±446

* To whom correspondence should be addressed. e-mail: [email protected]

Food Additives and Contaminant s ISSN 0265±203X print/ISSN 1464±5122 online # 2002 Taylor & Francis Ltdhttp://www.tandf.co.uk/journals

DOI: 10.1080/0265203011011379 9

largely subjective and often uninformed. In particu-lar, advocates who question organic techniques haveoften asserted that organic foods are as contaminatedwith pesticide residues as conventionally grown foods(Avery 2000, Stossel 2000, Milloy 2001).

In the past few years, EPA’s FQPA implementationeŒorts and related residue-monitoring programmes atthe US Department of Agriculture (USDA) havegenerated much new and more accurate data ondietary pesticide exposure (US EPA 2000d).Su� cient data currently exist to support rigorouscomparison of residues in organic, IPM-grown/NDR and conventional foods.

Before presenting such an analysis, it is useful tode®ne what we mean by òrganic’, ÌPM’, `NDR’and `conventionally grown’ foods. For our purposes,conventionally grown foods are de®ned, by default, asthose marketed with no claim that would qualifythem for one of the other categories. While werecognize that many non-organic or conventionalfarmers to some extent use IPM and even organicpest-management techniques, we classi®ed all pro-duce not marketed with a label or point-of-sale claimthat identi®es it otherwise, as conventionally grown.If any misclassi®cations resulted from this assump-tion, they would tend to reduce apparent diŒerencesbetween conventionally grown produce and presum-ably lower-residue alternatives.

Pesticides used by conventional growers (and others)are subject to multiple layers of federal and stateregulation, intended to protect farm workers, ensurefood safety, and minimize ecological eŒects of pesti-cide applications. Pesticides must be registered withthe EPA to be used on crops, and the EPA establishestolerances (legal maximum concentration limits) forresidues of each chemical on each crop for which it isregistered. About 600 diŒerent pesticide active ingre-dients are registered with the US EPA, and about10 000 food-use tolerances have been established.Pesticide use is regulated in terms of permitted cropsthat can be treated with any given chemical, amountsthat may be applied, and timing of applications.Applications may be restricted to allow an intervalbetween spraying and harvest, to allow residues todissipate to safe levels before the treated food reachesthe consumer.

Òrganic’ foods are de®ned by the USDA’s recentlypublished ®nal standard of identity for this foodcategory (USDA 2000a). National regulations weredeveloped to bring consistency to more than 40

diŒerent existing state and private sets of standards.In general, organic agriculture produces food withoutuse of synthetic chemicals. Some organic fruit andvegetable farmers, especially larger-scale producers,routinely apply certain natural pesticides derivedfrom botanical and mineral sources, and biologicalpreparations such as those containing the microbialinsecticide Bacillus thuringiensi s. (The national organ-ic standard de®nes `synthetic’ pesticides rather pre-cisely; pest-control substances outside those criteriaare, essentially by de®nition, `natural’ pesticides.)Organic farmers producing small grains, dry beans,corn, soybeans and forage crops typically do notapply any pesticides. A few synthetic pesticides arepermitted in organic agriculture; these are generallyexempt from an EPA tolerance (legal limit on residuesin foods) because of their low toxicity, expected lackof ecological or health risk, lack of expected dietaryresidues, or all of these reasons. The synthetic pesti-cides most commonly used in organic productioninclude sulphur, copper-based fungicides, oil sprays,insecticidal soaps, and insect pheromones (Walz andScowcroft 2000, OMRI 2001).

Organic farmers are allowed to use permitted pesti-cides only after non-pesticide interventions havefailed to control pests. Organic standards generallyrestrict applications of botanicals and allowed syn-thetic pesticides, to minimize impacts on the environ-ment and to reduce the likelihood of residues afterharvest in edible plant parts (OMRI 2001).

The ÌPM’ category encompasses many pest manage-ment technologies and systems now in use, whichshare a prevention-based approach. IPM systems relyheavily on scouting ®elds for pest population levelsand linking pesticide applications or other interven-tions to empirical evidence of economic damage. IPMinterventions include biological methods (such asnatural predators, parasites and pathogens) to keeppest populations within tolerable limits and multipletactics to promote vigorous crop growth and strongplant defence mechanisms (Benbrook et al. 1996).Current IPM systems range from some that are closeto organic systems in their reliance on bio-intensiveand cultural practices and avoidance of syntheticpesticides, to others that rely mainly on syntheticchemical biocides for pest management (Benbrooket al. 1996, Benbrook 2000, National ResearchCouncil 2000).

An increasing number of produce-labelling pro-grammes aimed at environmentally concerned con-sumers market foods as ÌPM-grown’. Typically these

428 B. P. Baker et al.

programmes require farmers to use certain recog-nized, biologically based and prevention-orientedIPM practices (Benbrook 2000), and some strictlylimit or prohibit the use of speci®c high-risk pesti-cides. Myriad `green labels’ have begun appearing onfoods in recent years, and the potential for consumerconfusion about the meaning and credibility of thediŒerent labels has increased as well. To address thisconcern, Consumers Union (CU, an independentconsumer product-testing and publishing organiz-ation in the USA) has developed an Internet databasewith descriptions and evaluations of the standardsand certi®cation procedures behind various foodecolabels (Consumers Union 2001).

Other foods are marketed with a `no detectable(pesticide) residues’ (NDR) claim. NDR foods aretested to certify that pesticide residues fall below a setlimit, usually 0.05 parts per million (ppm) (Scienti®cCerti®cation Systems 2001). For this analysis, weconsidered NDR and IPM-grown claims substantiallyequivalent and combined them into a single categorywe call ÌPM/NDR’.

Materials and methods, and data sources

We analysed pesticide residue data from three testingprogrammes, comparing the frequency of detectionand levels of pesticides found in foods produced withdiŒerent farming systems. We obtained residue datafrom the USDA’s Pesticide Data Program (PDP)(USDA 2000b), from the California Department ofPesticide Regulation (DPR’s) MarketplaceSurveillance Program (California EPA 1999), andfrom private tests on four selected foods carried outby CU (1998).

We obtained and analysed PDP residue data for testsdone in 1994±99. The PDP tests a small and changingselection of foods each year and samples each foodintensively, seeking accurately to represent the USmarket for the tested foods. Recent PDP tests haveincluded a few samples each year identi®ed at thepoint of sale as organically grown or carrying anIPM/NDR claim. In the 6 years of data obtained,the PDP tested 26 893 samples of fresh fruits andvegetables. Of those, 127 were identi®ed as organi-cally grown, and 195 were marketed with IPM/NDRclaims; the rest (26 571 samples) carried no recorded

market claim and were classi®ed for our analysis asconventionally grown.

We obtained California DPR data for the test years1989±98. DPR sampling in those 10 years included1097 identi®ed organic samples out of 67 154 totalsamples tested. The DPR programme does not iden-tify samples with IPM or NDR market claims.

CU tested just four foods (apples, peaches, greenpeppers, tomatoes), but the tests were designedspeci®cally to compare residue pro®les of foods fromthe three market sectors. CU’s tests included 67organically grown samples, 45 IPM/NDR samplesand 68 samples with no market claim.

Raw data were obtained from USDA, DPR, and CUand converted to Access data ®les keyed to uniquesample numbers. A series of queries were then used tocompute the number of samples, number with resi-dues, number of residues per positive sample, meanresidue levels in positive samples, and other resultsreported here. A statistician performed various ana-lyses to determine the statistical signi®cance of ob-served diŒerences.

Detailed descriptions of the sampling and analyticalmethods used in the PDP and DPR testing pro-grammes are available in published reports and ongovernment web sites (California EPA 1999, US FDA1999, 2000a, USDA 2000b, California DFA 2001).Discussion here focuses on selected characteristics ofeach data set most relevant to our analysis.

The PDP, established in 1990, is designed to provideestimates of pesticide residue levels and distribution inthe US food supply, to support dietary exposureassessments by the EPA and other regulatoryauthorities. Fresh fruits and vegetables purchased atretail comprise > 80% of PDP samples. Analyticalmethods include standard multiresidue methods(MRMs) used to screen for families of chemicals,and selected single-residue methods for individualpesticides of interest not picked up by the MRMs.Positive ®ndings are veri®ed with appropriate con-®rming methods. The low limits of detection (LODs)and rigorous quality-assurance procedures of thePDP produce what the EPA regards as the bestpesticide residue data available to support its riskassessments (US EPA 2000a±c).

PDP data diŒer markedly from `farm gate’ testing bythe US Food and Drug Administration (FDA) andstate departments of agriculture to enforce pesticidelabels and tolerance limits (US FDA 2000b). LODs in

429Pesticide residues in conventional, IPM-grown and organic foods

enforcement testing are typically much higher thanPDP LODs. The main goal of enforcement samplingis to detect residues over tolerance limits and divertfoods with illegal residues from the human foodsupply. This requires rapid turnaround of samplesand precludes using the highly sensitive methods andmultiple layers of quality control built into the PDP.We relied on PDP data, and did not include FDAdata, both because of the PDP’s better detectionsensitivity and more intensive sampling and becausethe FDA does not record market claims for the foodsit samples.

The DPR data set, by contrast, is from the largeststate enforcement programme in the US. As such,these data are subject to some of the limitations justdescribed above for the FDA data. However, DPRhas tested organic foods as a distinct market sectorsince 1989, and has more data on residues in organicsamples than any other available source.

The DPR programme collects samples of produce atpoints of entry, packing sites, wholesale facilities, andin retail outlets. Sampling within a food commoditymay be weighted based on relative intensity of pesti-cide use on a crop and on a history of violations froma region or particular supplier, and the number ofimported samples tested is greater than imports’relative market share. Thus, the DPR sampling isnot precisely representative of the market. Samplesare analysed by a California Department of Food andAgriculture (CDFA) laboratory using CDFA’sMRMs and selected single-residue methods for prior-ity pesticides. Methodologies and procedures for de-tecting pesticide residues have improved in generalover the years; and within the DPR data set, advancesin analytical methodology, particularly in 1991 and1996, increased the number of detectable pesticidesand decreased LODs (California EPA 1999).

CU’s tests were carried out by a contract laboratorywhose analytical methods closely parallel those usedby the PDP. Standard MRMs were used, and speci®cmethods were added for the ethylene bis-dithiocarbo-nate (EBDC) fungicides and benomyl (another fungi-cide), on selected foods. The LODs for CU’s testswere very similar to those reported by the PDP. CU’stesting focused on exploring diŒerences in residuepatterns between organically grown, IPM/NDR-la-belled and conventionally grown apples, peaches,green peppers and tomatoes. These four foods werechosen for testing because they are known to have ahigher than average likelihood of containing pesticideresidues. Samples were bought in a variety of retail

outlets in ®ve cities across the USA during summerand Fall of 1997 and shipped to the contract labora-tory for analysis. In all, 60 samples of apples, 30 ofpeaches, 30 of peppers and 60 of tomatoes weretested. Roughly equal numbers of organic, IPM/NDR and conventional samples were tested for eachfood, although IPM/NDR-labelled peppers and pea-ches were in limited supply.

Each of these three sets of residue data has strengthsand weaknesses. The PDP provides the highest qual-ity data, and its extensive sampling best represents theUS market for tested foods. But foods speci®callyidenti®ed as organically grown are underrepresentedin the PDP data set, accounting for < 0:5% of allsamples. Samples identi®ed as IPM/NDR are onlyslightly more numerous. Small numbers of samples ofspeci®c foods sold as organic or IPM/NDR tested inany given year limit analytical possibilities . The PDPalso does not test for some important residues in-cluded in CU’s and DPR’s testingÐin particular, theEBDC fungicides.

The DPR programme also samples the market verybroadly, although not precisely representatively .Within the DPR data set, the percentage of organicsamples is closer to the estimated US market share fororganic (about 2% of fresh produce according toUSDA 2000a); however, DPR does not speci®callyidentify samples with IPM/NDR claims. DPR analy-tical methods historically have had less sensitivedetection limits, and have therefore detected fewerresidues overall than methods used by PDP and CU.

The PDP and DPR data taken together provide abroad view across a wide array of diŒerent fruits andvegetables, purchased over a multi-year period andfrom a large, representative sample of locations with-in the USA and California, respectively. However,neither data set oŒers the depth of sampling neededfor convincing comparisons of residues in individualfoods as a function of market claim. The CU tests, incontrast, looked at just four foods purchased in a fewlocations over a short period. However, CU sampledeach food from each market sector in comparativedepth; the CU data generally include more organi-cally grown and IPM/NDR samples of each testedfood than the larger PDP and DPR data sets canprovide.

Collectively, the three data sets oŒer enough breadthto support general comparisons of residue patternsacross a wide range of diŒerent foods by marketclaim, and enough depth of sampling for a few foods


to support con®dence in the validity of observeddiŒerences in residue patterns in those speci®c foods.

One obvious gap in all three data sets is the lack oftesting for residues of botanical insecticides, such asrotenone and pyrethrum, and for residues of otherpesticides permitted for use on organic produce, suchas copper-based fungicides. The EPA and FDA donot consider most pesticides used in organic produc-tion to pose residue-related health risks, and they aretherefore not a priority to analyse. Botanical insecti-cides also tend to degrade rapidly in the environmentinto relatively non-toxic by-products. For these rea-sons, and perhaps also because of the relatively small(although rapidly growing) market share representedby organic foods in the USA, there has been littledemand here for analytical methods for residues ofthe natural insecticides. Few or no con®rmedmethods are available for these residues; conse-quently, they are generally not tested for by pro-grammes and laboratories that routinely monitorfoods for pesticides.

Analyses and results

We analysed the three pesticide residue data sets toexplore diŒerences in the frequency and levels ofpesticides in conventional, organic, and IPM/NDRfoods. We tested three hypotheses.

. Organic produce is less likely to have detectablepesticide residues than either IPM/NDR or conven-tionally grown produce.

. Among samples with any residues, conventionaland IPM/NDR foods are more likely to have mul-tiple residues in a given sample than organic foodsare.

. When present, residues in organic foods are likelyto be at lower levels than those in non-organicfoods.

When making residue comparisons, care must betaken in interpreting residues of persistent organo-chlorine (OC) insecticides banned many years ago.Examples include DDT, aldrin, dieldrin, heptachlor,chlordane and toxaphene (Edwards 1966). Carrots,potatoes and other root crops, cucurbits such assquashes and cucumbers, and selected leafy greens,such as spinach, tend to absorb OC residues from

soils and to translocate them into edible crop tissues(Nash 1974, Mattina et al. 2000, Groth et al. 2001).

While farmers can do little to eliminate these persis-tent residues from soils, they can select crops that areless likely to accumulate OCs from contaminated®elds. Additional steps can be taken as well. At leastone organic certi®er requires ®elds to be tested forOCs prior to certi®cation (Oregon Tilth 1999) andapplies standards based on relationships between OCresidues in soils and in speci®c crops, to ensure thatOC residues in harvested foods are below limits ofdetection (Tracy 1992, MacCormack et al. 1993).Nevertheless, OC residues are ubiquitous and willremain in soils and contaminate both conventionaland organic produce for decades. Our analysis ex-amined OC residues separately from other residues,to isolate this eŒect of general environmental con-tamination from diŒerences associated with currentproduction methods.

Frequency of positive samples

Our ®rst hypothesis is that organically grown foodsamples should have detectable pesticide residues lessoften than do conventionally grown or IPM/NDRsamples. The data in tables 1±4 were analysed usingCochran±Mantel±Haenszel (CMH) methods to deter-mine whether there were statistically signi®cant diŒer-ences in the frequency of detection of residues amongthe three market categories of foods.

Table 1 shows the number and per cent of samples offresh fruits and vegetables found to contain one ormore pesticide residues in PDP tests from 1994 to1999, arrayed by crop and market claim. PDP tested26 571 samples of conventionally grown (no marketclaim) fresh fruits and vegetables in those 6 years. Ofthese, 73% contained at least one pesticide residue;82% of fruit samples; and 65% of vegetables con-tained one or more residues. Celery, pears, apples,peaches and strawberries all had residues > 90% oftheir samples.

Over the same period, the PDP tested 195 samples offresh fruit and vegetables marketed with an IPM orNDR claim; 47% contained one or more residues,with modest diŒerences between fruits and vegetables.The diŒerence in overall per cent positive betweenconventional and IPM/NDR samples is highly statis-tically signi®cant (p < 0:001). A total of 193 distinctpesticide residues (including metabolites and isomers)


were found in the 91 positive samples of IPM/NDRfoods; 73 residues were at levels below the typicalNDR standard of 0.05 ppm. Accordingly, about two-thirds of the residues found in IPM/NDR foodssampled by PDP do not meet the most commonstandard for `NDR’, although some might meetdiŒerent criteria applied by various IPM-labellingprogrammes.

Only 23% of PDP organic samples contained one ormore residues. In this data set, organically grownsamples contained residues about one-third as oftenas conventional samples did, and half as often asIPM/NDR samples did. Both of these diŒerences arehighly statistically signi®cant (p < 0:001).

DiŒerences in percents positive between organic andconventional samples of apples, grapes, oranges, pea-ches, pears, strawberries, carrots, celery, cucumbers,

green beans, potatoes, spinach, peppers, sweet pota-toes and tomatoes were all also statistically signi®-cant, despite the small number of organic samples foreach individual food. The frequency of residues inIPM/NDR samples was statistically signi®cantly low-er than in conventional samples for 10 of these 15foodsÐall but strawberries, cucumbers, spinach,sweet potatoes and tomatoes.

If persistent organochlorine pesticides are removedfrom the comparison, the results change dramatically,particularly for vegetables. Table 2 repeats the com-parisons of PDP data in table 1, but with residues ofbanned OCs excluded. Banned OCs accounted forabout 40% of positive organic samples in table 1.With those contaminants excluded, the positive frac-tion of organic vegetables drops to 9%. IPM/NDRand conventionally grown vegetable samples showonly slight declines in per cent positive, and the per


Table 1. Frequency of pesticide residues in fresh fruits and vegetables by market claim: Pesticide Data Program, 1994±99.

Organic IPM/NDR No market claim

Number Number Per cent Number Number Per cent Number Number Per centof samples of positives positive of samples of positives positive of samples of positives positive

FruitsApples 1 0 ± 20 10 50 2294 2150 94Bananas 1 0 ± 11 4 36 1134 658 58Cantaloupe 3 1 33 0 0 ± 1242 603 49Grapes 4 1 25 12 4 33 1891 1481 78Oranges 7 1 14 13 7 54 1899 1616 85Peaches 2 1 50 10 5 50 1107 1035 93Pears 4 1 25 0 0 ± 1777 1689 95Strawberries 8 2 25 5 5 100 1268 1160 91All fruit 30 7 23 71 35 49 12 612 10 392 82

VegetablesBroccoli 2 1 50 18 7 39 674 171 25Carrots 18 4 22 21 7 33 1874 1359 73Celery 2 1 50 4 2 50 173 166 96Cucumbers 10 2 20 1 0 ± 723 533 74Green beans 3 0 ± 24 10 42 1169 689 59Lettuce 3 1 33 21 8 38 860 428 50Potatoes 4 1 25 20 10 50 1386 1117 81Spinach 19 9 47 7 7 100 1645 1380 84Sweet bell peppers 11 1 9 0 0 ± 722 500 69Sweet potatoes 6 1 17 1 1 100 1557 999 64Tomatoes 10 0 ± 5 4 80 1971 1254 64Winter squash 9 1 11 2 0 0 1205 497 41All vegetables 97 22 23 124 56 45 13 959 9093 65

All fresh foods 127 29 23 195 91 47 26 571 19 485 73

ÌPM/NDR’ includes `No Detectable Residues’ samples with the market claims `PDP No Pesticides Detected’, `PDP Pesticide Free’, `Speciality NoPesticides Detected’ and `Speciality Pesticide Free’. These market claims are typically accompanied by a requirement that integrated pest manage-ment systems also be used.Òrganic’ includes samples with the market claims `PDP Organic’ and `Speciality Organic’.

cent of positive fruit samples changes little in anymarket category when OC residues are excluded.Overall, excluding OC residues decreases the fractionof positive organic samples from 23 to 13%. As intable 1, the diŒerences among market claim categoriesshown in table 2 are all highly statistically signi®cant(p < 0:001).

As a practical matter, OC residues in organic foodsdo deserve to be counted, especially from the con-sumer’s perspective. However, this analysis suggeststhe extent to which the residues detected in manyorganic foods are associated with persistent environ-mental contamination, independent of contemporaryproduction methods.

Table 3 compares the frequency of residues detectedin organic and conventional foods sampled by theCalifornia DPR testing programme from 1989 to

1998. Because the DPR tests a very large number ofdiŒerent foods, only aggregated data, arranged bytest year, are displayed. Over the 10 years analysed,DPR tested 66 057 samples of conventional produce,of which 31% contained at least one residue. Only6.5% of 1097 DPR organic samples tested positive.This diŒerence is highly statistically signi®cant(p < 0:001). The higher LODs in DPR testing arethe primary reason why the percents positive are somuch lower here than in the PDP data, but therelative frequencies of detection in the two categoriesare highly comparable.

Table 3 also shows an apparent trend toward increas-ingly frequent detection of residues in both organicand conventional samples in recent years. Advancesin analytical methodology used by DPR, particularlyin 1991 and 1996, decreased LODs for many residues


Table 2. Frequency of pesticide residues in fresh fruits and vegetables by market claim, excluding the residues of bannedorganochlorines : Pesticide Data Program Results, 1994±99.


Number Number Per cent Number Number Per cent Number Number Per centof samples of positives positive of samples of positives positive of samples of positives positive

FruitsApples 1 0 ± 20 10 50 2294 2150 94Bananas 1 0 ± 11 4 36 1134 658 58Cantaloupe 3 1 33 0 0 ± 1242 514 41Grapes 4 1 25 12 4 33 1891 1477 78Oranges 7 1 14 13 7 54 1899 1616 85Peaches 2 1 50 10 5 50 1107 1035 93Pears 4 1 25 0 0 ± 1777 1689 95Strawberries 8 2 25 5 5 100 1268 1148 91All fruit 30 7 23 71 35 49 12 612 10 287 82

VegetablesBroccoli 2 1 50 18 7 39 674 170 25Carrots 18 0 0 21 7 33 1874 1137 61Celery 2 1 50 4 2 50 173 166 96Cucumbers 10 1 10 1 0 ± 723 499 69Green beans 3 0 ± 24 10 42 1169 684 59Lettuce 3 1 33 21 8 38 860 426 50Potatoes 4 1 25 20 10 50 1386 1078 78Spinach 19 2 11 7 7 100 1645 1212 74Sweet bell peppers 11 1 9 0 0 ± 722 500 69Sweet potatoes 6 1 17 1 1 100 1557 986 63Tomatoes 10 0 ± 5 2 40 1971 1253 64Winter squash 9 0 ± 2 0 0 1205 354 29All vegetables 97 9 9 124 54 44 13 959 8465 61

All fresh foods 127 16 13 195 89 46 26 571 18 752 71

See notes to table 1.Residues of long-banned organochlorine insecticides and their metabolites are not included: DDT, DDE, DDD, heptachlor epoxide, hexachlor-obenzene, aldrin and dieldrin.

and increased the number of detectable pesticides.This enhanced analytical sensitivity, rather thanchanges in pesticide use or other variables, is the mostlikely explanation for the observed increase in thefrequency of detectable residues.

We also analysed the DPR data with residues ofbanned organochlorines excluded. Results were simi-lar to those seen in table 2. Crops that accumulateOCs from soil occasionally had these residues,whether organic or conventional. Excluding the OCsreduced the per cent positive for the organic samplesmore noticeably than for the conventional samples.Because of the higher LODs in the DPR tests and thesmaller initial per cent of positive samples, the exclu-sion of OCs here had less eŒect than in the PDP data,but the overall picture was quite consistent.

Table 4 displays the frequency of residues found inthe four crops tested by Consumers Union. For allfour foods combined, 79% of conventional samples,51% of IPM/NDR samples and 27% of organicsamples had one or more residues. These overalldiŒerences are highly statistically signi®cant(p < 0:001). DiŒerences between the percents positivefor organic and conventionally grown samples of allfour individual foods were also statistically signi®-cant. The diŒerences between conventional and IPM/NDR samples were signi®cant for peppers and toma-toes, but not for apples and peaches. Positive percen-tages for conventionally grown individual foods inCU’s limited sampling were very similar to thosefound by the PDP with much larger, geographicall yand temporally more representative sampling of thesefoods.


Table 3. Frequency of residues in organic and conventional samples tested by the Calfornia Department of PesticideRegulation, 1989±98.

Organic No market claim

Total number Number of Number of Per cent Number of Number of Per centYear of samples samples positives positive samples positives positive

1989 9387 196 7 3.6 9191 2060 22.41990 8275 194 5 2.6 8081 1660 20.51991 7443 82 5 6.1 7361 1856 25.21992 7307 40 4 10.0 7267 2271 31.31993 6056 22 0 0.0 6034 2165 35.91994 5465 45 2 4.4 5420 1838 33.91995 5498 41 3 7.3 5457 1943 35.61996 6070 144 20 13.9 5926 2190 37.01997 5635 155 15 9.7 5480 2025 37.01998 6018 178 10 12.8 5840 2402 41.1

All years 67 154 1097 71 6.5 66 057 20 410 30.9

Table 4. Frequency of residues in fresh apples, peaches, peppers and tomatoes by market claim: Consumers Uniontesting.


Number of Number of Per cent Number of Number of Per cent Number of Number of Per centsamples positives positive samples positives positive samples positives positive

Apples 20 7 35 20 19 95 20 20 100Peaches 12 4 33 5 3 60 13 11 85Total fruit 32 11 34 25 22 88 33 31 94

Peppers 10 0 0 6 0 0 14 10 71Tomatoes 25 7 28 14 1 7 21 13 62Total vegetables 35 7 20 20 1 5 35 23 66

Total for the four foods 67 18 27 45 23 51 68 54 79

Multiple residues

Multiple pesticide residues are commonly detectedin several widely consumed fruits and vegetables.Samples of many foods commonly contain two,three or four diŒerent residues, and much highernumbers are not uncommon. For example, DPRtesting found 14 residues in a single green peppersample; the PDP has found as many on one spinachsample and 13 residues in a sweet bell pepper sample.US-grown apples tested by PDP in 1996 were morelikely to have four or more residues than they were tohave three or less, and were more than three times aslikely to have seven or more residues as they were tohave no residues. Multiple residues are also routinelyencountered on peaches, spinach, strawberries, pears,green peppers, cucumbers and celery, based on PDPresults.

Following a mandate of the FQPA, EPA has beenassessing cumulative exposures to pesticides thatshare a common mechanism of toxic action, such asthe organophosphate (OP) insecticides. A recent diet-ary exposure assessment for the OPs compiled by theUS EPA (2000c) reported that 998 (44%) of 2289samples of apples tested by PDP from 1994 to 1996contained at least one OP residue. Of the positivesamples, 419 (42%) had two OP residues, 67 (7%)had three, and seven (0.7%) had four. Overall,> 20% of apple samples contained two or more OPresidues. The same EPA analysis found that multipleOP residues were even more prevalent in canned andfrozen green beans, and in wheat grain, than inapples.

Our second hypothesis posits that when residues arepresent, organically grown samples are less likely tocontain multiple residues than conventionally grownor IPM/NDR samples are. Table 5 compares the

frequency of samples with multiple residues in eachmarket category by each of the three test pro-grammes. Numbers of residues in distinct samplesof 20 diŒerent foods (summarized in table 6) wereanalysed using CMH methods and a linear mixedmodel, to determine whether there were statisticallysigni®cant diŒerences in the average number of resi-dues in samples of each market category for eachfood.

In the PDP tests, 46% of conventional samples, 24%of IPM/NDR samples and just 7% of organicsamples had multiple residues. DPR found multipleresidues in 12% of conventional samples and about1% of organic samples. CU found multiple residuesin 62% of conventional, 44% of IPM/NDR and only6% of its organic samples. These diŒerences are allhighly statistically signi®cant (p < 0:001).

Further detail on numbers of residues in speci®cfoods is provided in table 6. PDP tests found 3.0residues on average in conventional apples, 2.9 resi-dues on conventionally grown peaches, 2.6 residueson conventional celery, strawberry, and sweet bellpepper samples, and 2.3 residues on conventionalpears. Organic samples had no residues or a singleresidue in 15 of 20 cases. One sample of òrganic’sweet bell peppers imported from Mexico containedsix residues. (This sample was clearly mislabelled, andnot organically grown; see table 7). The IPM/NDRsamples, while intermediate between organic andconventionally grown produce in the odds of havingany residues at all, had almost as many residues inpositive samples as conventional samples did for mostfoods, and in a few cases, had more. The lower overallfrequency of multiple residues in the IPM/NDRcategory relative to conventional produce appears tore¯ect the lower overall per cent positive for thissector, more than fewer residues per positive sample.


Table 5. Samples containing multiple residues by market claim in three datasets.


Samples Per cent Samples Per cent Samples Per centNumber with samples Number with samples Number with samples

of multiple multiple of multiple multiple of multiple multipleData set samples residues residues samples residues residues samples residues residues

PDP (20 crops) 127 9 7.1 195 46 23.6 26 571 12 102 45.5DPR (19 crops) 609 8 1.3 n.a. n.a. n.a. 34 003 4 055 11.9CU (four crops) 67 4 6.0 45 20 44.4 68 42 62

n.a., Not applicable.


Table 6. Number of pesticide residues found by market claim and average number of residues in fresh foods tested by theUSDA’s Pesticide Data Program, 1994±99.

No. of No. of No. of unique Residues per Residues persamples tested positive samples residues found sample tested positive sample

ApplesNo market claim 2294 2150 6967 3.0 3.2Organic 1 ± ± ± ±IPM/NDR 20 10 38 1.9 3.8

BananasNo market claim 1134 658 728 0.6 1.1Organic 1 ± ±IPM/NDR 11 4 4 0.4 1.0

BroccoliNo market claim 674 171 190 0.3 1.1Organic 2 1 1 0.5 1.0IPM/NDR 18 7 7 0.4 1.0

CantaloupeNo market claim 1242 603 940 0.8 1.6Organic 3 1 1 0.3 1.0IPM/NDR ± ± ±

CarrotsNo market claim 1874 1359 2655 1.4 2.0Organic 18 4 4 0.2 1.0IPM/NDR 21 7 10 0.5 1.4

CucumbersNo market claim 723 533 1421 2.0 2.7Organic 10 2 4 0.4 2.0IPM/NDR 1 ± ±

CeleryNo market claim 173 166 449 2.6 2.7Organic 2 1 1 0.5 1.0IPM/NDR 4 2 3 0.8 1.5

GrapesNo market claim 1890 1481 3536 1.9 2.4Organic 4 1 1 0.3 1.0IPM/NDR 12 4 8 0.7 2.0

Green beansNo market claim 1169 689 1504 1.3 2.2Organic 3 ± ±IPM/NDR 24 10 33 1.4 3.3

LettuceNo market claim 860 428 792 0.9 1.9Organic 3 1 1 0.3 1.0IPM/NDR 21 8 10 0.5 1.3

OrangesNo market claim 1899 1616 2996 1.6 1.9Organic 7 1 1 0.1 1.0IPM/NDR 13 7 13 1.0 1.9

PeachesNo market claim 1107 1035 3233 2.9 3.1Organic 2 1 1 0.5 1.0IPM/NDR 10 5 12 1.2 2.4

(continued)

Residue levels

Our third hypothesis states that when residues arepresent in organically grown foods, they should be atlower concentrations than the residues typicallyfound in conventionally grown and IPM/NDR foods.This hypothesis is di� cult to test using most statis-tical methods, because the relative rarity of residues inorganic foods leaves few degrees of freedom to testsigni®cance. One practical approach is to compare thesame residues on the same crops (e.g. chlorpyrifos ontomatoes) across market categories. We call any givencomparison of this sort a crop±pesticide data pair(CPDP). While comparing residues of conventionalpesticides on organic foods (typically the result of

inadvertent contamination or mislabelling) with thesame residues on conventional or IPM/NDR crops(typically the result of deliberate crop treatment)might seem biased toward ®nding lower residues inorganic produce, it is in fact the most practical way tocompare residues, since the data on residues in or-ganic foods are essentially all for residues of conven-tional pesticides.

Excluding OC residues, there are 22 organic-conven-tional CPDPs in the PDP data, 25 in the DPR dataand seven in the CU data. The PDP data provide onlyeight organic-IPM/NDR CPDPs, but there are 70IPM/NDR-conventional PDP CPDPs. The CU dataset contains ®ve organic-IPM/NDR CPDPs, and ®veIPM/NDR-conventional CPDPs. Across all three


Table 6Ðconcluded

No. of No. of No. of unique Residues per Residues persamples tested positive samples residues found sample tested positive sample

PearsNo market claim 1777 1689 4091 2.3 2.4Organic 4 1 2 0.5 2.0IPM/NDR ± ± ±

PotatoesNo market claim 1386 1117 1806 1.3 1.6Organic 4 1 1 0.3 1.0IPM/NDR 20 10 20 1.0 2.0

SpinachNo market claim 1645 1380 3193 1.9 2.3Organic 19 9 16 0.8 1.8IPM/NDR 7 7 18 2.6 2.6

StrawberriesNo market claim 1268 1160 3326 2.6 2.9Organic 8 2 3 0.4 1.5IPM/NDR 5 5 12 2.4 2.4

Sweet bell peppersNo market claim 722 500 1854 2.6 3.7Organic 11 1 6 0.5 6.0IPM/NDR ± ± ±

Sweet potatoNo market claim 1557 999 1324 0.9 1.3Organic 6 1 1 0.2 1.0IPM/NDR 1 1 1 1.0 1.0

TomatoesNo market claim 1971 1254 2938 1.5 2.3Organic 10 ± ±IPM/NDR 5 4 4 0.8 1.0

Winter squashNo market claim 1205 497 783 0.6 1.6Organic 9 1 1 0.1 1.0IPM/NDR 2 ± ±

data sets, typically just one or a very few organic orIPM/NDR samples contained a particular residue, somean residues in the organic and IPM/NDR samplesoften re¯ect a single value. In contrast, the number ofpositive conventional samples with a given residue isgenerally larger.

Small numbers of organic and IPM/NDR sampleswith speci®c residues limit the statistical power ofcomparisons for individual CPDPs. However, statis-tically meaningful conclusions can be extracted fromthe data as a whole. The data in tables 7±10 wereanalysed using two types of statistical tests. Residueconcentrations were directly compared using log-transformed concentrations or ranks, or using a linearmixed model controlling for crop, year or data set asappropriate. Tests were also performed for equality ofproportion of pairs where conventional samples had ahigher concentration, using Friedman’s Rank test,exact tests for proportions, and À2-tests.

Table 7 presents the 22 organic-conventional CPDPsin the PDP data set. Residues in organic samples werelower in 15 cases (68%). This diŒerence falls just shortof being statistically signi®cant (p ˆ 0:067). Of the

eight organic-IPM/NDR CPDPs in the PDP data(not shown in table 7), the IPM/NDR samples hadhigher residues in ®ve cases (62%). This diŒerence isnot signi®cant.

Table 8 compares residues in IPM/NDR samples withthose in corresponding conventional samples in thePDP data set. IPM/NDR samples are much morelikely to contain residues than organic samples are,and there are 70 of these CPDPs. Residues in IPM/NDR samples were lower than those in the conven-tional samples in 48 cases (69%). This diŒerence ishighly statistically signi®cant (p ˆ 0:002).

Table 9 shows 25 conventional-organic CPDPs in theDPR data set; organic samples had lower residues in15 cases (60%). This diŒerence is of borderline sta-tistical signi®cance (p ˆ 0:059). In interpreting table9, it should be recalled that the LODs of the DPRanalytical methods are higher than those of the othertwo data sets. Since the DPR tends to detect onlycomparatively higher residues, the odds that an or-ganic sample would have a much lower residue thanmight occur in a conventional sample are reducedfrom the outset.


Table 7. Comparison of organic and no market claim mean residues found in 22 crops, USDA data.

No market claim Organic samples Ratio nomarket claim

Number of Mean residue Number of Mean residue to organicFood Active ingredient positives (ppm) positives (ppm) mean

Broccoli DCPA 142 0.014 1 0.007 2.0Cantaloupe methamidophos 64 0.050 1 0.021 2.4Celery oxamyl 28 0.087 1 0.11 0.8Cucumber endosulphan I 319 0.023 1 0.008 2.9Grape iprodione 746 0.233 1 0.14 1.7Grape vinclozolin 197 0.147 1 0.2 0.7

Orange formetanate HCL 86 0.422 1 0.3 1.4Peach endosulphans 49 0.029 1 0.01 2.9Pear diphenylamine 340 0.094 1 0.017 5.5Pear o-phenylphenol 327 0.845 1 0.037 22.8Potato chlorpropham 892 1.59 1 1.6 1.0Spinach DCPA 30 0.011 1 0.007 1.5Spinach methamidophos 43 0.009 1 0.072 0.1Spinach omethoate 225 0.069 1 0.008 8.6Spinach permethrin 946 1.920 1 0.49 3.9Strawberry iprodione 287 0.552 1 0.079 7.0Strawberry methomyl 162 0.440 1 0.19 2.3Strawberry chlorpryifos 5 0.006 1 0.007 0.9Sweet bell pepper endosulphan I 148 0.030 1 0.008 3.8Sweet bell pepper methamidophos 260 0.092 1 0.68 0.1Sweet bell pepper diazinon 6 0.012 1 0.061 0.2Sweet potato o-phenylphenol 14 0.031 1 0.017 1.8


Table 8. Comparison of ÌPM/NDR’ claim sample means to `no market claim’ samples in 70 crop pesticide data pairstested by the USDA’s Pesticide Data Program.

No market claim IPM/NDR Ratio nomarket claim

Number of Mean residue Number of Mean residue mean residueFood Active ingredient positives (ppm) positives (ppm) to IPM/NDR

Apple azinphos methyl 1148 0.0568 1 0.0200 2.84Apple benomyl 67 0.1047 5 0.1064 0.98Apple captan 287 0.1160 1 0.0700 1.66Apple chlorpyrifos 514 0.0255 2 0.0050 5.09Apple dicofol 32 0.3005 1 0.1400 2.15Apple dimethoate 126 0.0470 2 0.0300 1.57Apple diphenylamine (DPA) 1370 0.7973 9 0.7078 1.13Apple methomyl 61 0.0358 2 0.0675 0.53Apple omethoate 94 0.0241 2 0.0400 0.60Apple oxamyl 93 0.0325 1 0.0500 0.65Apple phosmet 127 0.0500 1 0.0100 5.00Apple propargite 526 0.3944 4 0.4375 0.90Apple thiabendazole 1100 0.8389 7 0.5176 1.62Banana thiabendazole 577 0.0927 4 0.0938 0.99Broccoli DCPA 142 0.0141 7 0.0131 1.08Carrot acephate 4 0.0110 1 0.0060 1.83Carrot captan 11 0.0191 1 0.0200 0.95Carrot iprodione 525 0.0455 1 0.1000 0.45Carrot tri¯uralin 733 0.0524 5 0.0228 2.30Celery chlorothalonil 117 0.0889 2 0.3250 0.27Celery permethrin 50 0.0769 1 0.1800 0.43Grape captan 678 0.1621 3 0.3467 0.47Grape dimethoate 256 0.0624 1 0.0180 3.46Grape iprodione 746 0.2334 3 0.1397 1.67Grape omethoate 243 0.0428 1 0.0900 0.48Green bean acephate 247 0.2623 5 0.2576 1.02Green bean benomyl 73 0.3048 3 0.1980 1.54Green bean carbaryl 41 0.2492 3 0.4267 0.58Green bean carbofuran 2 0.0200 1 0.0100 2.00Green bean chlorothalonil 177 0.0911 6 0.0502 1.82Green bean DCPA 54 0.0449 2 0.0940 0.48Green bean dimethoate 69 0.1576 2 0.4500 0.35Green bean endosulphans 305 0.1387 3 0.0493 2.81Green bean iprodione 21 0.3220 1 0.1000 3.22Green bean methamidophos 234 0.1046 5 0.0618 1.69Green bean omethoate 43 0.0405 2 0.0950 0.43Lettuce acephate 116 0.0306 1 0.0080 3.83Lettuce endosulphans 140 0.0426 5 0.0216 1.97Lettuce methamidophos 54 0.0092 1 0.0090 1.02Lettuce mevinphos 76 0.0469 1 0.0250 1.87Lettuce permethrin 95 0.3796 2 0.1165 3.26Oats, rolled malathion 17 0.0054 1 0.0050 1.07Orange ethion 32 0.0112 1 0.0020 5.58Orange formetanate HCL 86 0.4216 1 0.0850 4.96Orange imazalil 1051 0.1297 5 0.1958 0.66Orange thiabendazole 1056 0.2026 6 0.2323 0.87Peach azinphos methyl 288 0.0792 1 0.0500 1.58Peach benomyl 187 0.4160 3 0.4100 1.01Peach captan 135 0.1539 1 0.0100 15.39Peach carbaryl 167 0.4062 1 0.1200 3.39Peach dicloran 411 0.7614 2 0.0160 47.59Peach iprodione 779 0.8885 3 0.3533 2.51

(continued)


Table 8Ðconcluded

No market claim IPM/NDR Ratio nomarket claim

Number of Mean residue Number of Mean residue mean residueFood Active ingredient positives (ppm) positives (ppm) to IPM/NDR

Peach parathion methyl 302 0.0548 1 0.0480 1.14Potato chlorpropham 892 1.5910 8 1.1570 1.38Potato endosulphans 216 0.0143 5 0.0056 2.56Potato o-phenylphenol 44 0.1724 1 0.0250 6.90Potato thiabendazole 290 0.4253 5 0.3168 1.34Spinach dimethoate 100 0.2726 1 0.0180 15.14Spinach endosulfans 86 0.1161 1 0.0100 11.61Spinach omethoate 225 0.0686 2 0.0885 0.78Spinach permethrin 946 1.9199 7 0.8556 2.24Strawberry captan 761 1.1084 1 0.1200 9.24Strawberry iprodione 584 0.5787 3 0.3820 1.51Strawberry malathion 162 0.0324 3 0.0427 0.76Strawberry methomyl 322 0.4176 1 0.9100 0.46Strawberry myclobutanil 263 0.0954 2 0.1380 0.69Strawberry vinclozolin 167 0.4774 2 0.1390 3.43Sweet potato dicloran 898 0.3536 1 0.3200 1.10Tomato chlorthalonil 158 0.0875 2 0.0425 2.06Tomato piperonyl butoxide 13 0.2923 2 0.0840 3.48

Table 9. Comparison of organic and no market claim mean residues found in 25 crop pesticide data pairs tested by theCalifornia Department of Pesticide Regulation, 1994±98.

No market claim Organic Ratio nomarket claim

Number of Mean of Number of Mean of mean toCrop Active ingredient positives positives (ppm) positives positives (ppm) organic mean

broccoli DCPA 9 0.05 1 0.06 0.83cabbage chlorpyrifos 4 0.14 1 0.17 0.82cabbage dimethoate 2 0.15 1 0.10 1.45cabbage methamidophos 6 0.19 2 0.22 0.89cucumber endosulphan 308 0.12 2 0.05 2.66grape endosulphan 7 0.06 1 0.31 0.18grape iprodione 41 0.64 1 1.76 0.36grape methomyl 29 0.41 1 0.14 2.90lettuce chlorothalonil 4 0.10 1 0.11 0.89lettuce DCPA 13 0.13 3 0.03 4.21lettuce endosulphan 29 0.32 1 0.04 7.94lettuce, leaf DCPA 22 0.06 1 0.19 0.32onion, green chlorothalonil 29 0.55 1 0.05 10.90orange chlorpyrifos 304 0.14 1 0.10 1.44pear methyl parathion 4 0.03 1 0.04 0.73pepper carbaryl 59 0.75 1 0.10 7.46pepper chlorothalonil 3 0.12 1 0.07 1.71pepper endosulphan 168 0.15 2 0.12 1.28pepper methamidophos 642 0.20 1 0.54 0.36pepper methomyl 41 0.21 1 0.35 0.59spinach DCPA 5 0.21 1 0.06 3.43spinach permethrin 261 1.69 2 1.26 1.34squash, summer endosulphan 248 0.10 2 0.02 6.77tomato chlorothalonil 106 0.49 1 0.11 4.46tomato methamidophos 425 0.11 1 0.10 1.07

Table 10 summarizes CPDPs from the CU data.Organic samples had lower residues in ®ve of sevenorganic-conventiona l pairings (71%). Organicsamples had lower residues than IPM/NDR samplesin two of ®ve cases (40%), and IPM/NDR sampleshad lower residues than conventional samples in fourof those ®ve CPDPs (80%). Because of the smallnumber of cases in this data set, none of the diŒer-ences in table 10 are statistically signi®cant.

Overall, a clear picture emerges from the CPDPcomparisons across all three data sets. In each case,residues in organic samples were lower than the sameresidues in conventional samples about two-thirds ofthe time. While these diŒerences within each indi-vidual data set failed to achieve statistical signi®canceat the p < 0:05 level, aggregating the three data setsimproves the power of the analysis. The combineddata sets include 54 conventional-organic CPDPs; theorganic samples had lower residues in 37 cases (69%),a result that is statistically signi®cant (p ˆ 0:029).

The comparison of IPM/NDR-conventional CPDPsincludes 70 from the PDP data set, and an additional®ve from CU’s data. Combining the two sets yields atotal of 53 cases on which the residues are lower inIPM/NDR samples (71%), and modestly increasesstatistical con®dence in this result (p ˆ 0:001).

Discussion

The three data sets oŒer test results obtained bygovernment agencies and by an independent consu-mer organization, none of which have any commer-cial or institutional interest in organic, IPM/NDR orother market claims. The data support robust, objec-

tive comparisons of pesticide residues in foods pro-duced with diŒerent agricultural methods andmarketed with various claims. Our analysis showsconvincingly that organic samples are much less likelyto contain detectable pesticide residues than conven-tionally grown or IPM/NDR foods are. Organicsamples with residues are also far less likely to havemultiple residues than are conventional or IPM/NDRsamples. These diŒerences are clear-cut, consistentacross data sets, and highly statistically signi®cant.

Fewer data exist to permit direct comparisons ofresidue levels in organic and non-organic samples ofa given crop, because of the small number of organicsamples in any data set that have a speci®c pesticideon a speci®c food. However, here, too, when data areexamined from all three data sets, a consistent patternemerges: organic samples in paired comparisons hadlower residues about two-thirds of the time. Thispattern was consistently observed across a wide rangeof diŒerent foods tested by all three programmes,suggesting that it is quite likely generally true fororganic foods as a whole.

The two data sets that include IPM/NDR foodsamples as an identi®able market sector also supportthe conclusion that, despite the heterogeneous natureof the category, samples that carried an IPM or NDRclaim generally were less likely to contain residues andhad lower residues than were found in conventionallygrown samples. The IPM/NDR samples also hadmore frequent and generally higher residues thanthose in organic samples.

Current risk assessment methodologies cannot de®ni-tively quantify the possible public-health implicationsof pesticide residues in the diet. A consensus nowexists, at least within the USA, that dietary pesticideresidues are a signi®cant public health concern, par-


Table 10. Comparison of organic and IPM/NDR mean residues to no market claim mean residues in seven and ®ve croppesticide data pairs tested by the Consumers Union.

No market claim IPM/NDR Organic Ratio no RatioRatio IPM/ market IPM/NDR

Number Mean of Number Mean of Number Mean of NDR to claim to to noActive of positives of positives of positives organic organic market

Crop ingredient positives (ppm) positives (ppm) positives (ppm) mean mean claim mean

Apple azinphos methyl 10 0.103 21 0.073 3 0.032 2.3 3.2 0.71Apple carbaryl 2 0.055 0 2 0.029 1.9Apple thiabendazole 10 0.804 5 0.125 2 0.042 3.0 19.1 0.16Apple benomyl 5 0.076 14 0.077 2 0.078 1.0 1.0 1.01Peach phosmet 4 0.63 2 0.147 1 3.3 0.0 0.2 0.23Peach benomyl 4 0.067 0 2 0.051 1.3Tomato benomyl 8 0.078 1 0.06 6 0.064 0.9 1.2 0.77

ticularly for young children (National ResearchCouncil 1993). Nevertheless, the available evidencefalls short of associating speci®c harm to individualswith routine exposure to dietary pesticide residues.

Despite these irreducible scienti®c uncertainties, risksare relative, and exposure to fewer and lower dietaryresidues should translate into smaller risks. Ouranalysis therefore supports the conclusion that therisks posed by organically grown fruits and vegetablesare substantially smaller than comparable risks fromfoods grown using conventional pest managementsystems. Foods produced under an IPM or NDRlabelling regime appear to fall in between conven-tional and organic foods in terms of residues andrisks.

There is a signi®cant gap in this qualitative riskcomparison, related to the possible contribution tototal risk of residues of natural pesticides. This cate-gory includes the botanical insecticides, such as rote-none, pyrethrum and pyrethrins, sabadilla and neem;bio-based insecticides such as Bacillus thuringiensis;and mineral-based products, including horticulturaloils and sulphur and copper-based fungicides. Whilesuch natural pest management tools are commonlyassociated with organic farming, many are also usedby conventional farmers and IPM practitioners. Thelack of residue data noted earlier in this paper, andthe lack of complete toxicological data for mostbotanical insecticides, have seriously limited abilityto carry out risk assessments for these pest-manage-ment products. These constraints aŒect not onlyassessments of risks associated with organic foods,but also assessments of any similar risks posed by useof these products in conventional and IPM-basedfarming.

Some commentators, in particular habitual US criticsof organic agriculture, have suggested that unmea-sured, toxicologically untested, theoretical residues ofnatural pesticides in organically grown foods renderorganic foods as `hazardous’ in terms of residue-related health risks as conventionally grown foods(D. T. Avery 2000, A. Avery 2001, Stossel 2000,Milloy 2001). This claim is neither supported byempirical data nor scienti®cally credible, but it hasbeen widely spread through the mass media, such thatquestions related to natural pesticides have becomesomething of a cloud accompanying the generallyaccepted silver lining of fewer conventional pesticideresidues in organically grown foods.

Several lines of indirect evidence suggest that residuesof natural pesticides are rarely present or pose mini-mal health concerns in any market category of foodson which they might be used. As noted in ourdescription of organic foods earlier in this paper,organic farming rules require that any pesticides usedare applied minimally, and only as a last resort, andapplication rates allowed on organic farms are typi-cally lower than those allowed on conventionallygrown crops (Meister 1999). In a survey of pesticideuse by the Organic Farming Research Foundation,52% of organic growers said they `never’ used bota-nical insecticides, another 21% reported using theseproducts `rarely’, and only 9% said they used them`frequently or regularly’ . Even fewer organic farmersuse sulphur or copper-based fungicides or horticul-tural oils, with 60%, 66% and 65% saying they`never’ use these products, respectively (Walz 1999,Walz and Scowcroft 2000).

Most of the popular natural pesticides are used pri-marily because they pose minimal ecological threatsto farming systems. Other natural but highly toxicpesticides, such as nicotine, cryolite, strychnine andlead arsenate, are banned from organic productionand rarely used by farmers in other categories.Sulphur and copper compounds, horticultural oilsand insecticidal soaps are far less toxic and consideredsafe based on long experience. Most pesticides com-monly used on organic farms are exempt from EPAtolerances (i.e. no safety-based residue limits aredeemed necessary), because of low toxicity or a lowprobability of detectable residues in foods, or both.(Banned natural pesticides are covered in 7 CFR 602.The exempt status of sulfur and related naturalfungicides are listed in 40 CFR 180.2; petroleum oilsin 40 CFR 180.1001(b)(3). Copper compounds areexempted from EPA tolerances in 40 CFR180.1001(b)(1) and exempted are permitted for usein organic farming in 7 CFR 205.601(i)(1). Pyrethrumand pyrethrins are exempted from tolerances in 40CFR 180.1001(b)(6) ; rotenone, derris or qube roots in40 CFR 180,1001(b)(7); sabadilla in 40 CFR180.1001(b)(8) ; and azadirachtin, the active constitu-ent of neem, in 40 CFR 180.1119. ) The botanicalinsecticides generally break down quickly in the en-vironment. For example, rotenone degrades rapidly insunlight (Mandava 1985), and pyrethrum and itsderivatives also decompose rapidly (Casida 1973).The belief that most botanicals rapidly break downexplains both the lack of EPA tolerances and the lackof analytical methods for residues; the EPA has


concluded that residues of these compounds are un-likely to be present in foods.

Recent research has suggested that rotenone, injecteddirectly into rats, has neurotoxic eŒects (Betarbet et al.2000). The EPA has assessed the possible carcino-genicity of pyrethrum and concluded that this naturalinsecticide (derived from chrysanthemums) may posesome cancer risk for humans (Avery 2001). It seemsessential that the widely used botanicals be morecompletely tested for the full range of toxic eŒectsthat conventional pesticides are currently tested for.Expanded eŒorts to collect data on possible residuesof the natural pesticides in organic and non-organicfoods are also needed. Better toxicity data and residuedata will improve the basis for risk assessments ofthese pest-management tools. If future research veri-®es health concerns related to certain of the botani-cals, for example, their continued useÐin bothorganic and non-organic farmingÐwould need to bere-evaluated. Ultimately, debate over the theoreticalrisks of these pesticides is likely to persist until a solidbody of empirical data clearly resolves the issue.

For the present, however, there is no basis to con-clude that residues of natural pesticides in any foods,organic or conventional, pose risks remotely compar-able to those represented by residues of conventional(synthetic) pesticides. The toxicity of the organopho-sphate and carbamate insecticides, for example, hasbeen quite thoroughly tested. Upper limits of `safe’exposure have been de®ned by regulatory authorities,based on risk assessments with extensive peer reviewand comments from interested parties (Groth et al.2001). The presence of frequent residues of many ofthe widely used synthetic insecticides in foods hasbeen well documented, and residue levels often ap-proach or exceed o� cial `safe’ doses (Groth et al.2000, 2001). In contrast, there are simply no crediblescienti®c data to indicate either that signi®cant resi-dues of natural pesticides are present in foods, or thatresidues of these substances that might be presentpose a meaningful public health risk. Nevertheless,these are certainly interesting questions, and it is ineveryone’s interest to see better scienti®c answersdeveloped.

Returning to a topic on which we have data, virtuallyall the residues detected in organic foods (and othermarket categories of foods) by the three test pro-grammes are residues of conventional, synthetic pes-ticides. How and why do residues of syntheticpesticides get into organic foods? Many of theseresidues do not violate organic standards, which

recognize that small amounts of residues from sourcesbeyond farmers’ control are unavoidable. The USNational Organic Program (NOP) standard for un-avoidable contamination is 5% of the applicable EPAtolerance. Most residues detected in positive organicsamples in all three of our data sets were well belowthis level and would not have disquali®ed the testedsamples from being accurately labelled and sold asorganic under that standard.

A few positive organic samples, however, containedmore signi®cant residues. For example, one sample ofpeaches labelled organic, tested by CU, contained3.3 ppm of phosmet, explainable only as the resultof spraying shortly before harvest. An importedorganic sweet bell pepper sample tested by the PDPin 1999 contained high residues of methamidophos,diazinon, methyl parathion and endosulphan.Methamidophos was found in this sample at 0.68ppm, compared with a mean level of 0.092 ppm in260 positive conventional pepper samples (table 7).These two samples may have been mislabelled asorganic where they were sold, or perhaps misidenti-®ed as organic in data-entry errors within the testprogrammes.

Mislabelling of organic samples can result from wilfulfraud or an inadvertent lapse in chain-of-custodyaccounting. To the consumer, the reason matterslittle. Such incidents appear rare, from data examinedhere. Nevertheless, the organic community, particu-larly certifying agents and government enforcementagencies, needs to develop eŒective procedures forinvestigating and rectifying even isolated high-residueincidents.

Some other positive organic samples seem likely tore¯ect post-harvest contamination of organicallygrown samples. For example, many of the organictomato samples tested by CU had benomyl residuescomparable to those in conventionally grownsamples. Residues could have resulted from fungicidetreatment during transport or storage, or mixing oftreated and untreated produce somewhere betweenfarm and retail, as well as from possible mislabelling.

Pesticide residues in foods sold as organic are groundsfor a fraud investigation under the US NOP rule. Wereviewed data from such investigations related tosome of the 71 organic samples found to containresidues in the California DPR data. Firm conclu-sions could not be reached in any given case, butfraud, chain-of-custody errors by the grower or ship-per, or laboratory error may explain some relatively


high positive samples. In about half the cases, how-ever, residues were very low and consistent withunavoidable environmental contamination becauseof drift, persistent residues in the soil, or contami-nated irrigation water supplies.

Implementation of the NOP ®nal standards shouldfurther reduce the frequency and levels of conven-tional pesticides in organic foods. The new regula-tions prohibit use on organic crops of all syntheticpesticides that have EPA tolerances, and limit una-voidable contamination to 5% of the EPA tolerance.Foods with residues exceeding these limits may notlegally be sold as organic. New national standards foraccreditation of private and state organic certi®ersshould increase the consistency of industry practices,help avoid detectable residues and enhance the like-lihood that mislabelled foods will be detected anddealt with. Farmers will also face greater sanctionsand penalties for mislabelling of food as organic.Certi®ers have a mandate to collect samples forpesticide analysis, and when crops contain residuesabove acceptable limits, certi®ers must investigate andimpose sanctions. Future accreditation of certi®erswill depend, at least in part, on how eŒectively theyenforce these provisions.

Our analysis shows that food samples marketed withIPM/NDR claims consistently had fewer and lowerpesticide residues than conventionally grown samples,but more frequent and higher residues than organicsamples. In this case, the presence of residues ofconventional synthetic pesticides is expected, sinceIPM and conventional systems employ largely over-lapping arsenals of chemicals. Nevertheless, someresidues detected in IPM/NDR samples may indicateeither mislabelling or unavoidable environmentalcontamination, as for organically grown samples.

Are IPM/NDR-labelled foods more like òrganic’,more like `conventional’ , or a distinctive category intheir own right? Based on data from the CU and PDPtests, IPM/NDR foods are intermediate between theother two categories in terms of frequency of residues.With respect to multiple residues, positive IPM/NDRsamples are very much like positive conventionalsamples. In terms of the relative residue levels, themedian ratio for organic-conventiona l CPDPs andthe median ratio for IPM/NDR-conventional CPDPsare highly similar (1.50 and 1.58, respectively).Overall, IPM/NDR foods may be an attractive alter-native for consumers interested in reducing theirexposure to pesticide residues. At this point, IPM/NDR is an eclectic and relatively new category, whose

precise market share is not well documented. Themany labelling programmes in this category havediŒerent criteria for certi®cation and diŒerent degreesof rigour in their requirements, making the credibilityof individual programmes di� cult for consumers toassess. Confusion over proliferation of `green labels’on foods may eventually generate pressure for uni-form US national standards, as have evolved fororganically grown foods.

Conclusions, research needs and policy implications

The present analysis shows convincingly, using threedistinct measures applied to three separate data sets,that organically grown foods contain fewer pesticideresidues than conventional or IPM-grown foods, andthat residues, when present, are lower in organicfoods. We hope this objective analysis of reliableempirical data will help resolve some questions aboutdiŒerences in pesticide residue pro®les between or-ganic and non-organic foods. We have also shownless striking but similar diŒerences between conven-tional foods and IPM/NDR labelled produce, andbetween IPM/NDR and organic foods.

The data suggest that consumers who seek to reducetheir exposure to pesticide residues can do so reliablyby choosing organic produce, and to a lesser degreeby choosing IPM/NDR-labelled fruits and vegetables.However, none of the choices available on the marketis completely free of pesticide residues. Organicallygrown produce contains some residues of syntheticpesticides, consistent with unavoidable contaminationfor the most part. Some small fraction of foods soldas organic also appears to be mislabelled convention-ally grown produce. Unavoidable residues and occa-sional mislabelling and the often-higher prices oforganic foods are factors consumers can weigh asthey make food purchase decisions.

More data are needed to re®ne and update thesecomparisons. Sampling of both organic and IPM/NDR foods tested by the major pesticide monitoringagencies should be expanded, to better represent thepresence of these foods in the marketplace. There is aparticular need for data on possible residues ofbotanical and other natural pesticides on both organ-ic and non-organic produce. The hypothesis that suchresidues might be present and could oŒset to a degreethe comparative lack of synthetic pesticide residues in


organic produce should be either con®rmed or re-jected on the basis of robust empirical data.

The relative lack of synthetic pesticides in organicproduce shown by the data presented here makesintuitive sense, since such foods are not supposed tohave such chemicals applied to them. Residues that`should not be there’ (excluding unavoidable environ-mental residues of the OC insecticides) were detectedin 13% of the organic samples tested by the PDP.Reducing this level of contamination will be a sig-ni®cant challenge for the organic agricultural sector.On one hand, most of the residues found re¯ect thecapacity of wind, rain, fog, and irrigation water tomove pesticides beyond the ®elds where they wereapplied. On the other hand, better procedures andclearer policies are needed to help ensure that the newUS organic regulations can achieve their stated pur-pose of making organically grown foods essentiallyfree of detectable residues.

One possible policy mechanism for strengthening thecapacity of the organic community to isolate andeliminate residues in organic food would be to setup a national alert system. The USDA NOP couldreceive a notice from the PDP and state laboratorieswhenever an organic sample was found to contain aresidue. The NOP, certi®ers and enforcement agenciescould then track down and rectify the source of theproblem.

Active management to limit crops grown on soilcontaminated with persistent organochlorine pesti-cides can signi®cantly reduce that source of contam-ination. EŒective strategies have been documented(Oregon Tilth 1999) but are not included in theNOP rule and need to be more widely adopted.Farmers who grow crops such as carrots, wintersquash, spinach, and other foods known to accumu-late organochlorine pesticides may need to take spe-cial precautions, including testing their ®elds for soil-bound OC residues. Mandating such steps, at least fororganic food, may well be justi®ed from a publichealth perspective and should be added to organicindustry quality control procedures.

The IPM/NDR category is still quite young, andgrowing rapidly. It appears that consumer demandfor low-pesticide foods signi®cantly exceeds the cur-rent capacity of organic farming in the USA, and thatboth organic and IPM/NDR categories may continueto grow vigorously as long as minimizing residueexposure remains a consumer concern. To earn con-sumer con®dence over the long-term, IPM/NDR

Labeling programmes need to develop rigorous andtransparent standards and certi®cation procedures.Whether national standards for IPM/NDR Labelingwill ultimately be required may depend on howsuccessfully the industry can address these needsand coordinate disparate programmes without federalregulation.

For conventional farmers in both the USA and incountries that export fruits and vegetables to theUSA, continued implementation of the FQPA willincrease pressures to eliminate or to markedly reduceresidues of high-risk pesticides in foods, especiallyfoods that are prominent in children’s diets. If theFQPA goal of an increased safety margin is met,residues in conventionally grown foods will trenddownward toward levels currently found in someIPM/NDR foods. Tighter residue limits and reducedpesticide use by conventional growers should alsoreduce drift incidents and other sources of unavoid-able environmental contamination. These factors mayprompt organic producers to make even greater ef-forts to avoid residues, so that the organic label canmaintain its distinctive promise of relatively lowerpesticide exposure and risk.

The market shares for both organic and IPM/NDRproduce seem likely to continue to grow in comingyears. These trends, coupled with growing reliance onbiological interactions and prevention-based pestmanagement systems, should reduce both overallpesticide use and residues in food and water, withconcomitant reductions in risks to farm workers andagricultural ecosystems. Consumers and all who workwithin the food system should share the bene®ts.

Acknowledgements

The authors thank W. Keith Newsom-Stewart, SeniorStatistician, Consumers Union, for his many insightsand invaluable contribution in carrying out statisticalanalyses of the data. The authors also recognize thecontribution of Cynthia J. Langlois, formerly aProject Leader in the Public Service Projects depart-ment at the Consumers Union (and currently with theWeinberg Group, San Francisco), who led the CUtest project in 1997. They are grateful to TerrySchmer of the California EPA, Department ofPesticide Regulation, and Martha Lamont, PesticideData Branch Chief, USDA Pesticide Data Program,


for their cooperation and assistance in helping theauthors obtain and interpret the DPR and PDP data,respectively. Any errors of interpretation are theauthors’ alone.

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