Analysis of Pesticides in Food and Environmental Samples - Chapter 5 pdf

TABLE 5.1Major Sources of Random and Systematic Errors in Pesticide Residue Analysisa Sampling Wrong sampling design or operation Inhomogeneity of analyte in sampled object Degradation,

5 Quality Assurance

Árpád Ambrus

CONTENTS

5.1 Introduction 125

5.1.1 Quality Systems 126

5.1.2 Characterization of the Uncertainty and Bias of the Methods 127

5.1.2.1 Uncertainty of the Measurement Results 128

5.1.2.2 Systematic Error—Bias of the Measurements 130

5.2 Sampling 132

5.2.1 Quality of Samples 132

5.2.2 Sampling of Commodities of Plant and Animal Origin 134

5.2.3 Estimation of Uncertainty of Sampling 135

5.3 Sample Preparation and Processing 136

5.4 Stability of Residues 138

5.4.1 Stability during Storage 138

5.4.2 Stability of Residues during Sample Processing 139

5.5 Method Validation 141

5.5.1 Internal Quality Control 142

5.6 Interlaboratory Studies 146

References 147

5.1 INTRODUCTION

The results of measurements should provide reliable information and the laboratory should be able to prove the correctness of measurements with documented evidence Analysts carry serious responsibilities to produce correct and timely analytical results, and are fully accountable for the quality of their work The expanding national and international trade, the responsibility of national registration authorities permitting the use of various chemicals required long ago reliable test methods, which were acceptable by all parties concerned The accuracy and precision of the

are developed to assist the analysts to apply the relevant analytical quality control

guidance for accreditation purposes The Codex Committee on Pesticide Residues

which also includes detailed information on the minimum criteria for validation of

GLP Principles,and can be freely downloaded from the Internet

5.1.1 QUALITYSYSTEMS

The Good Laboratory Practice (GLP) is a quality system concerned with the izational processes and the conditions under which nonclinical health and environ-mental safety studies are planned, performed, monitored, archived, and reported

Guide25 and EN 45001), contains all the general requirements for the technicalcompetence to carry out tests, including sampling, that laboratories have to meet

if they wish to demonstrate that they operate a quality system, and are able to generatetechnically valid results It covers analytical tasks performed using standard methods,nonstandard methods, and laboratory-developed methods, and incorporates all thoserequirements of ISO 9001and ISO 9002 that are relevant to the scope of the services

simultaneously, and they are specifying basically the same requirements in terms

of AQC

The quality assurance (QA) program aimed at achieving the required standard of

study conduct and designed to assure test facility management that the analyses ofsamples or conduction of the studies comply with the established procedures.Measurements of any type contain a certain amount of error This error com-ponent may be introduced when samples are collected, transported, stored, andanalyzed or when data are evaluated, reported, stored, or transferred electronically

It is the responsibility of quality assurance programs to provide a framework fordetermining and minimizing these errors through each step of the sample collection,analysis, and data management processes The process must ensure that we do the

deliver quality Staff must be trained, involved with the tasks in such a way thatthey can contribute their skills and ideas and must be provided with the necessaryresources Accreditation of the laboratory by the appropriate national accreditationscheme, which itself should conform to accepted standards, indicates that thelaboratory is applying sound quality assurance principles

of the quality assurance program, which must also include the staff training,

* Co-operation on International Traceability in Analytical Chemistry.

y International Standard Organisation.

z International Electrotechnical Commission.

§

Organization for Economic Co-operation and Development.

administrative procedures, management structure, auditing, and so on The tory shall document its policies, systems, programs, procedures, and instructions to

shall be communicated to, understood by, available to, and implemented by theappropriate personnel

The laboratory shall have quality control procedures* for monitoring thebatch to batch validity, accuracy, and precision of the analyses undertaken Meas-urement and recording requirements intended to demonstrate the performance ofthe analytical method in routine practice The resulting data shall be recorded insuch a way that trends are detectable and, where practicable, statistical tech-niques shall be applied for evaluating the results This monitoring shall be planned

performing replicate tests using the same or different methods; and retesting ofretained items.1

The analytical methods must be thoroughly validated before use according torecognized protocol These methods must be carefully and fully documented, staffadequately trained in their use, and control charts should be established to ensure

fi-ciency test programs does not replace the establishment of within laboratory

international standards by applying calibrated equipment and analytical standards

requir-ing tests with special methodology and expertise to well-established and experienced(preferably accredited) laboratories, than to invest a lot of time, instruments, and so

on to set up and maintain a validated method (and experience to apply it) forincidental samples in a laboratory

provides laboratories with an objective means to demonstrate their capability ofproducing reliable results

5.1.2 CHARACTERIZATION OF THEUNCERTAINTY ANDBIAS OF THE METHODSThe interpretation of the results and making correct decisions require information onthe accuracy and precision of the measurements The measurement process is

the uncertainty (repeatability, reproducibility) and trueness of the measurementresults

* Synonymous with the term analytical quality control (AQC) and performance veri fication.

5.1.2.1 Uncertainty of the Measurement Results

The uncertainty of the measurements is mainly due to some random effects The

This is a different concept to measurement error (or accuracy of the result) which can

noting that, while the overall random error cannot be smaller than any of its uting sources, the resultant systematic error can be zero even if each step of thedetermination of the residues provides biased results Another important differencebetween the random and systematic errors is that once the systematic error is quanti-fied the results measured can be corrected for the bias of the measurement, whilethe random error of a measurement cannot be compensated for, but its effects can bereduced by increasing the number of observations

where

ciand ckare the sensitivity coefficients

u(xi,yk) is the covariance between xiand yk(i6¼ k)

u(xi,xk)¼ u(xi)3 u(xk)3 rik

The uncertainty components of a residue analytical result may be grouped

evapor-ation, derivatizevapor-ation, instrumental determination) The major sources of the randomand systemat ic errors 13 are summari zed in Tab le 5.1 The ir nature and contr ibution tothe combined uncertainty of the results will be discussed in the following sections

CVRes¼ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiCV2

Sþ CV2 L

q

and CVL¼ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiCV2

Spþ CV2 A

q

laboratory phase including sample processing (Sp) and analysis (A) The preparation

gentle rinsing or brushing to remove adhering soil, or taking outer withered looseleaves from cabbages) cannot be usually validated and its contribution to the uncer-tainty of the results cannot be estimated If the combined uncertainty is calculated from

TABLE 5.1

Major Sources of Random and Systematic Errors in Pesticide Residue Analysisa

Sampling Wrong sampling design or operation Inhomogeneity of analyte in sampled object

Degradation, evaporation of analytes during preparation, transport and storage

Varying ambient (sample material) temperature during transport and storage Varying sample size

Nonhomogeneity of the analyte in single units of the analytical sample Sample processing Decomposition of analyte during sample processing,

cross-contamination of the samples

Nonhomogeneity of the analyte in the ground =chopped analytical sample Variation of temperature during the homogenization process

Texture (maturity) of plant materials affecting the ef ficiency

of homogenization process Varying chopping time, particle size distribution Extraction =cleanup

Quantitative

determination

Incomplete recovery of analyte

Interference of coextracted materials (load of the adsorbent) Interference of coextracted compounds

Incorrectly stated purity of analytical standard Biased weight =volume measurements Determination of substance which does not originate from the sample (e.g., contamination from the packing material)

Determination of substance differing from the residue definition

Variable derivatization reactions Varying injection, chromatographic and detection conditions (matrix effect, system inertness, detector response, signal-to-noise variation, etc.)

Operator effects (lack of attention) Calibration

the linear combination of the variances of its components, according to the Welch–Satterthwaite formula the degree of freedom of the estimated uncertainty is

4 c(y)

validation, or from the results of reanalysis of replicate test portions of samples

materials are not suitable for this purpose as they are thoroughly homogenized

vut

effects by the recovery studies The repeatability of instrumental determination,which does not take into account the effect of preparation of calibration from

determin-ation of the total uncertainty of the predicted concentrdetermin-ation based on the

require special software to avoid tedious manual calculations

5.1.2.2 Systematic Error—Bias of the Measurements

The systematic errors can occur in all phases of the measurement process However,

Once the sample is taken, the most accurate and precise determination of the

residues in the treated material can be carried out with radiolabeled compounds.Unfortunately, routine pesticide residue laboratories very rarely have access to facil-ities suitable for working with radioisotopes Nevertheless, very useful information on

which are published annually by FAO, and can be freely downloaded from the

Web site of the Pesticide Management Group Another source of information is thedata submitted to support the claim for registration of the pesticides Though the

made accessible for laboratories analyzing pesticide residues

Alternately, laboratories may test the bias of their measurement results withperforming recovery studies usually spiking the test portion of the homogenized

born in mind that the recovery tests can provide information on the systematic errorand precision of the procedure only from the point of spiking Thus, following theusual procedure it will not indicate the loss of residues during storage and sampleprocessing The recovery studies are normally performed with untreated samples

detectable response, the analyte equivalent of the average instrument signal obtainedfrom the unspiked sample shall be taken into account When the average recovery is

currently some regulatory authorities require results which are not adjusted for therecovery It may lead to a dispute situation when parties testing the same lot applyingmethods producing different recoveries For instance, the shipment may be simplyrejected due to the lower recoveries of analytical method used in the exportingcountry Another area, where reporting the most accurate result is necessary, isproviding data for the estimation of exposure to pesticide residues In this case the

different from 100% In order to avoid any ambiguity in reporting results, when acorrection is necessary, the analyst should give the uncorrected as well as the

the corrected results CVAcor¼ ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiCV2

correction should be avoided as far as practical

subjected to random variation If the procedural recovery performed with an tical batch is within the expected range, based on the mean recovery and within-laboratory reproducibility of the method, the analyst demonstrated that the methodwas applied with expected performance Therefore, the correct approach is to use thetypical recovery established from the method validation and the long-term perform-

measured residue values, if necessary

Under certain circumstances, such as extraction of soil samples, the extractionconditions cannot be fully reproduced from one batch of samples to the next, leadingoccasionally to much higher within laboratory reproducibility than repeatability

(3Sr< SR) In this case, the use of concurrent recovery for adjusting the measuredresidues may provide more accurate results Where correlation between the residuevalues observed, the uncertainty of the residue value adjusted for the recovery should

be calculated according to Equation 5.1 Where correlation between the results is

analytical batch covering the expected residue range, and use their average valuefor correction to reduce the uncertainty and improve the accuracy of the results

5.2 SAMPLING

The analytical results cannot be better than the sample which is analyzed Eventhough the importance of reliable sampling has long been recognized, the majority ofregulatory laboratories concentrated only on the validation and establishing perform-ance characteristics of the methods Very little attention was paid to the quality of the

situation requiring the incorporation of sampling uncertainty in the combined tainty when relevant

uncer-Methods of sampling for the analysis of pesticide residues cannot be validated

commodity or object can only be assured by careful planning of the samplingprogram, providing clear instructions for the actual sampling operation includingpacking and shipping of samples

The sampling method depends on the objectives of the analysis, and hence thesampling plan and protocol should be prepared jointly by the managers making

taking the samples The objectives of the investigation and the corresponding

5.2, will determine the size, frequency (time or distance), spacing, mixing, dividing

of samples, and consequently the time required for sampling and the cost of

is a key component of designing sampling plans

The information on the uncertainty of sampling, subsampling, and sampleprocessing is equally important as the information on the uncertainty of analyses

5.2.1 QUALITY OFSAMPLES

the characteristic properties) a part of the object that is representative and suitable foranalysis The part of the object taken for further examination is the sample which is

* One or more units taken from one position in a lot.

composite bulk sample, from which the laboratory sample may be prepared The test

extracted

To prepare such a small fraction of the sampled object providing unbiased

the test portions analyzed should satisfy some basic quality requirements:

particle size distribution)

properties the object had at the time of sampling; be suitable to givethe required information (e.g., mean composition, composition as a func-tion of time or place); and keep its identity throughout the whole procedure

To develop a quality sampling plan, the following actions should be taken and pointsmay be considered:

want to obtain information on the average residue in a commodity or the

fields)

(it may be necessary to inspect the site to determine the conditions andequipment required)

containers to be used to collect, pack, and ship the samples, taking also intoaccount the health, safety, and security precautions

handling the samples

all stages, including size reduction of bulk sample

record to the laboratory in unchanged conditions, and assuring integrity ofthe whole operation

to collect and record all essential information including deviations from thesampling protocol

of the operation and the provisions to be taken for obtaining reliable

the particular conditions, recording requirements, legal actions, etc.)

5.2.2 SAMPLING OFCOMMODITIES OFPLANT ANDANIMALORIGIN

For testing compliance with maximum residue limits (MRL), the CCPR elaborated a

MRL for a plant, egg, or dairy product refers to the maximum level permitted tooccur in a composite bulk sample,* which has been derived from multiple units ofthe treated product, whereas the MRLs for meat and poultry refers to the maximumresidue concentration in the tissues of individual treated animals or birds Each

minimum number of primary samples to be taken depends on the size of the lot.Each primary sample should be taken from a randomly chosen position as far as

laboratory sample(s) required The primary samples should be combined and mixedwell, if practicable, to form the bulk sample Where the bulk sample is larger than is

portion A sample divider, quartering, or other appropriate size reduction processmay be used but units of fresh plant products or whole eggs should not be cut orbroken Where units may be damaged (and thus residues may be affected) by theprocesses of mixing or subdivision of the bulk sample, or where large units cannot bemixed to produce a more uniform residue distribution, replicate laboratory samplesshould be withdrawn or the units should be allocated randomly to replicate labora-tory samples at the time of taking the primary samples In this case, the result to beused should be the mean of valid results obtained from the laboratory samplesanalyzed

Further details for the minimum mass and the number of primary samples to betaken depending on the size of the sampled lot or the targeted (acceptable) violationrate are given in the guidelines

Samples taken for residue analysis in supervised trials are usually larger than

the average residues Sample may be taken from the experimental site randomly, or

should be taken at different time intervals after the application of the pesticide forestablishing decline curves, the least variation can be obtained if the primary

and the primary samples are collected from the close vicinity of the marked positions

* For products other than meat and poultry, the combined and well-mixed aggregate of the primary samples taken from a lot For meat and poultry, the primary sample is considered to be equivalent to the bulk sample.

y A quantity of a food material delivered at one time and known, or presumed, by the sampling of ficer to have uniform characteristics such as origin, producer, variety, packer, type of packing, markings, consignor, and so on.

z The sample sent to, or received by, the laboratory A representative quantity of material removed from the bulk sample.

5.2.3 ESTIMATION OFUNCERTAINTY OFSAMPLING

As it was shown, the average residues and CV of residues in individual crop units in

units, e.g., oranges) taken repeatedly from the same parent population (e.g., from afield or a lot) may vary significantly The best estimate of the uncertainty of sampling

The sampling uncertainty depends on the size of composite samples and thedistribution of residues in the sampled commodity Based on 174 residue data sets

There were no data for estimation of the uncertainty of sampling cereal grains, eggs,and processed products The variation of residues in composite samples taken from

residues in composite samples ranged between 80% and 120% The data evaluation

TABLE 5.2

Typical Sampling Uncertainty for Various Fresh Plant Commodities

with Lower (LC) and Upper (UC) Confidence Intervals

Confidence Limits of CV Styp

The ISO Standard 11648-1 for sampling bulk materials28recommends to applyfully nested or staggered nested experimental design to obtain information on theuncertainty of withdrawing the bulk samples from different lots, reducing the samplesize with subsampling (sample preparation) and analysis The procedures are illus-

informa-tion about the variability of the analyte, ~20 lots should be sampled, preferablyseveral pairs of samples taken from each lot

Sampling of the same residue data population by withdrawing random composite

very similar results for the average residue and the average CV of the residues Forinstance, even if 30 pairs of random composite samples of size 10 were withdrawn

100 times from a data population having a CV of 0.28, the minimum and maximum

CV values observed were 0.205 and 0.365, respectively, which is in agreement with

Concerning the sampling uncertainty, one should always remember that theMRLs refer to the residues in the bulk sample Hence, for testing compliance with

the sampling uncertainty need not be taken into account On the other hand, where

uncertainty must be included in the combined expanded uncertainty of the measuredresidue value

5.3 SAMPLE PREPARATION AND PROCESSING

require removal of foreign materials and certain parts of the sampled material(such as shell of nuts, stone of mango or peach, adhering soil, outer withered looseleaves in case of plant materials, and peddles and remains of plants from soil, etc.)

Fully nested experiment Staggered nested experiment

validated and their contribution to the uncertainty of the results cannot be estimated,the sample preparation procedure should be clearly written and consistently followedwithout any deviation to obtain comparable results.

The residues in individual crop units are not uniformly distributed Therefore thewhole laboratory sample must be prepared and the entire analytical sample should bechopped, ground, or mixed to obtain a well-mixed material from which the repre-sentative test portions can be withdrawn for extraction The large crops making up

the limited capacity of the equipment In these cases, representative portions should

be cut from the individual units in such a way that the ratio of the surface and innerpart remains the same

matur-ity, and variety of the crops, but it is independent of the concentration and nature of

plant materials with hard peal and soft pulp (tomato) than from a soft fruit (orange).The homogeneity (well-mixed status) of the processed analytical sample cannot be

alternative is to treat a small portion of the sample matrix with the test compound

evaluating the results with ANOVA The scheme of the process is very similar to that

the size of the test portion If the expectable uncertainty should be determined for agiven range of test portion size to optimize the analytical procedure, the concept of

where m is the mass of a single increment and CV is the relative standard deviation

of the concentration of the analyte in the test portions of size m

If the analytical sample is well-mixed, the sampling constant should be the samefor small (Sm) and large (Lg) portions, and Equation 5.5 can be written as

If the ratio of S2

SmmSm=S2

sample can be considered well-mixed, and the expected sample processing

The acceptable variability of sample processing depends on the variability ofthe other steps of the determination When the combined uncertainty of the meas-