Manual of pesticide residue analysis, volume 2

DFG

Manual of Pesticide
Residue Analysis
Volume II

VCH


© VCH Verlagsgesellschaft mbH, D-6940 Weinheim (Federal Republic of Germany), 1992
Distribution:
VCH, P.O. Box 101161, D-6940 Weinheim (Federal Republic of Germany)
Switzerland: VCH, P.O. Box, CH-4020 Basel (Switzerland)
United Kingdom and Ireland: VCH (UK) Ltd., 8 Wellington Court, Cambridge CB1 1HZ (England)
USA and Canada: VCH, 220 East 23rd Street, New York NY 10010-4606 (USA)
ISBN 3-527-27017-5 (VCH, Weinheim)

ISBN 0-89573-957-7 (VCH, New York)


DFG Deutsche Forschungsgemeinschaft

Manual of Pesticide
Residue Analysis
Volume II
Edited by Hans-Peter Thier
and Jochen Kirchhoff
Working Group "Analysis"

Pesticides Commission

VCH


Deutsche Forschungsgemeinschaft
Kennedyallee 40
D-5300 Bonn 2
Telefon: (0228) 885-1
Telefax: (0228) 8852221

Published jointly by
VCH Verlagsgesellschaft mbH, Weinheim (Federal Republic of Germany)
VCH Publishers Inc., New York, NY (USA)

Translators: J. Edwards t and Carole Ann Traedgold

Library of Congress Card No. applied for.

A catalogue record for this book is available from the British Library.

Deutsche Bibliothek Cataloguing-in-Publication Data:
Manual of pesticide residue analysis / DFG, Deutsche Forschungsgemeinschaft, Pesticides Commission.
Ed. by Hans-Peter Thier and Jochen Kirchhoff. [Transl.: J. Edwards and Carole Ann Traedgold]. Weinheim; Basel (Swizerland); Cambridge; New York, NY: VCH.
NE: Thier, Hans-Peter [Hrsg.]; Deutsche Forschungsgemeinschaft / Kommission fur Pflanzenschutz-,
Pflanzenbehandlungs- und Vorratsschutzmittel
Vol. 2 (1992)
ISBN 3-527-27017-5 (Weinheim ...)
ISBN 0-89573 957-7 (New York)

© VCH Verlagsgesellschaft mbH, D-6940 Weinheim (Federal Republic of Germany), 1992
Printed on acid-free and chlorine-free paper.

All rights reserved (including those of translation into other languages). No part of this book may be
reproduced in any form - by photoprinting, microfilm, or any other means - nor transmitted or
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to be considered unprotected by law.
Composition: Filmsatz Unger & Sommer GmbH, D-6940 Weinheim. Printing: betz-druck Gmbh,
D-6100 Darmstadt 12
Printed in the Federal Republic of Germany


Preface
During more than two decades, the Working Group on Pesticide Residue Analysis of the
"Senatskommission fur Pflanzenschutz-, Pflanzenbehandlungs- und Vorratsschutzmittel"
(Pesticides Commission), Deutsche Forschungsgemeinschaft (DFG), has edited a loose-leaf
Manual of residue analytical methods.
All the methods contained in this Manual were validated prior to their publication, by at
least one independent laboratory. Therefore, the Manual has met with acceptance far beyond
the frontiers of the Federal Republic of Germany, particularly since many of the methods are
included in the List of Recommended Methods of Analysis issued by the Codex Committee
on Pesticide Residues (CCPR) of the FAO/WHO Codex Alimentarius Commission. Many
residue analysts are, however, not well versed in German. Therefore, to overcome this language
barrier and to render the methods accessible to a far wider international circle of analysts,
the Working Group decided to translate the most important sections of the Manual into
English. This mission was sponsored by the Deutsche Forschungsgemeinschaft.
Volume 1 of the English edition was published in 1987. It contained 23 compound-specific
("single") analytical methods selected from the 6th and 7th instalments (issued in 1982 and
1984, respectively) of the German edition, 17 multiresidue analytical methods and 6 cleanup
methods (both 1984 status) as well as all pertinent general sections, e. g. on the collection and
preparation of samples, on the limits of detection and determination, and on micro methods
and equipment for sample processing.

The present Volume 2 of the English edition is a direct continuation and completion of the
first volume. It contains 32 single methods, many of them designed for the determination of
recently developed compounds. These methods were adopted, in most cases, from the 8th to
11th instalments of the German edition issued between 1985 and 1991. Furthermore, Volume 2
contains five new multiresidue analytical methods (coded S) published in German since the
first volume went to press, and some tables providing supplementary data on the broad applicability of Methods S 8 and S 19 and Cleanup Method 6, both described in Volume 1.
Special features of Volume 2 are Part 5, presenting six multiple methods for analysis of
residues in water (coded W), and Part 6 on analytical methods for determining residues in
water using the Automated Multiple Development (AMD) technique. Moreover, two new
cleanup methods for the solid-phase extraction of water samples on alkyl-modified silica gel
are included. An additional chapter introduces a new concept for deriving the limits of detection and determination by the calibration curve technique, thus providing a commendable
alternative to the procedure proposed in Volume 1. Finally, a comprehensive table gives massspectrometric El data for confirmation of gas-chromatographic results. In some cases, the
Editorial Committee has also partly changed or updated the original German version in order
to better adjust it to the needs of today's methodology. A cumulative index for Volumes 1 and
2 provides easy access to all pertinent compounds and information.
The Working Group on Pesticide Residue Analysis had hoped that it would render a major
contribution to pesticide residue analytical methodology by carrying on the German and
English editions. However, the Working Group had to terminate its activities in 1989, after
so many years of engagement in matters of pesticide residue analysis, because the Senate of


VI

Preface

the DFG modified the basic structures of its advisory commissions with the consequence that
the mandate of the Pesticides Commission and its Working Groups expired.
Nevertheless, the Editorial Committee (J. Kirchhoff (chairman), H. Frehse, H.-G. Nolting,
H.-P. Thier) was charged, by the DFG, with the commitment to finalize any going publication
activities. Thus, the Committee first edited the last, 11th Instalment (issued 1991) of the German Manual on the basis of the validated methods that had become available yet by 1989.

Next, the Editorial Committee did its very best to compile Volume 2 of the English edition.
Parts of it are based on the very competent contributions of the late James Edwards (died
1987) who had translated the text of Volume 1. The remaining text was basically translated
by Carole Ann Traedgold and edited by the Committee.
The Editorial Committee hopes that this two-volume compilation of procedures and
methods will prove useful to all concerned with the analysis of pesticide residues.


Contents
Contents of Volume 1
Senate Commission for Pesticides, Deutsche Forschungsgemeinschaft
Working Group on Residue Analysis, Senate Commission for Pesticides
Part 1: Introduction and Instructions (contd.)
Derivation of the Limits of Detection and Determination Applying the Calibration
Curve Concept
Mass-Spectrometric El Data for Confirmation of Results
Part 2: Cleanup Methods (contd.)
Cleanup Method 6. Cleanup of crude extracts from plant and animal material by gel
permeation chromatography on a polystyrene gel in an automated apparatus
(updated)
Cleanup Method 7. Solid phase extraction of water samples on alkyl-modified silica gel
using disposable columns
Cleanup Method 8. Solid phase extraction of water samples on alkyl-modified silica gel
Part 3: Individual Pesticide Residue Analytical Methods (contd.)
Amitrole, 4-A*)
Anilazine, 186
Benomyl, Carbendazim, Thiophanate-methyl, 261-378-370
Bitertanol, 613-A
Bitertanol, Triadimefon, Triadimenol, 613-425-605
Bromoxynil, Ioxynil, 264-212

Carbendazim, 378
Carbosulfan, Carbofuran, 658-344
Chlorflurenol, Flurenol, 275-215
Chloridazon, 89-A
Chlorsulfuron, Metsulfuron, 664-672
Copper Oxychloride, 147-A
Cymoxanil, 513
2,4-D, Dichlorprop, 27-A-38-A
Dichlobenil, 225-A
Dichlofluanid, Tolylfluanid, 203-371
Dichlofluanid, Tolylfluanid, 203-A-371-A
Dinobuton, Binapacryl, 255-8
Fonofos, 288
Fosetyl, 522

IX
XI
XV

3
25

31
37
41
49
59
69
77
87

99
107
113
127
135
145
153
157
163
169
177
191
197
205
211

*) Code numbers according to which the analytical methods are identified in the German issue of the
Manual. The number without affixed letter corresponds to the BBA registration number of the individual compound.


VIII

Contents

Glufosinate, 651
Glyphosate, 405
Metaldehyde, 151-A
Metribuzin, 337
Nitrothal-isopropyl, 416
Oxamyl, 441

Phenmedipham, 233-B
Propachlor, 310
Propiconazole, 624
Sulphur, 184-B
Thiabendazole, 256-A
Thiabendazole, 256-B

217
229
239
245
253
261
269
275
281
287
291
295

Part 4: Multiple Pesticide Residue Analytical Methods (contd.)
Pesticides, Chemically Related Compounds and Metabolites Determinable by the
Multiresidue Methods in Parts 4 to 6: Supplement to the Table of Compounds,
pp. 221 ff, Vol. 1
S 8 Organohalogen, Organophosphorus and Triazine Compounds (updated)
S 19 Organochlorine, Organophosphorus, Nitrogen-Containing and Other Pesticides
(updated)
S 22 Natural Pyrethrins, Piperonyl Butoxide
S 23 Pyrethroids
S 24 Organotin Compounds

S 25 Methyl Carbamate Insecticides
S 26 Phthalimides

317
323
333
343
349
359

Part 5: Multiple Pesticide Residue Analytical Methods for Water
W 4 Phenoxyalkanoic Acid Herbicides
W 5 Fungicides
W 6 Organochlorine Insecticides
W 7 Phenoxyalkanoic Acid Herbicides
W 8 Triazine Herbicides
W 13 Desalkyl Metabolites of Chlorotriazine Herbicides

369
377
387
393
403
413

Part 6: Pesticide Residue Analytical Methods for Water Using the AMD Technique
Thin-Layer Chromatographic Analysis of Pesticides and Metabolites Using the
Automated Multiple Development (AMD) Technique
Examples for Applying the AMD Technique to the Determination of Pesticide Residues
in Ground and Drinking Waters

Cumulative Indexes for Volumes 1 and 2
Index of Determinable Pesticides, Metabolites and Related Compounds (Index of Compounds)
Index of Analytical Materials
List of Suppliers Referenced in the Text-Matter of the Manual
Author Index

301
313

423
435

449
459
479
483


Contents of Volume 1
Senate Commission for Pesticides, Deutsche Forschungsgemeinschaft
Members and Guests of the Working Group on Residue Analysis, Senate Commission for
Pesticides
Part 1: Introduction and Instructions

Explanations
Notes on Types and Uses of Methods
Important Notes on the Use of Reagents
Abbreviations
Preparation of Samples
Collection and Preparation of Soil Samples

Collection and Preparation of Water Samples
Use of the Term "Water"
Micro Methods and Equipment for Sample Processing
Limits of Detection and Determination
Reporting of Analytical Results
Use of Forms in the Reporting of Analytical Results
Part 2: Cleanup Methods

Cleanup Method 1. Separation of organochlorine insecticides from hexachlorobenzene and
polychlorinated biphenyls
Cleanup Method 2. Cleanup of crude extracts from plant and animal material by sweep codistillation
Cleanup Method 3. Cleanup of crude extracts from plant material by gel permeation chromatography on Sephadex LH-20
Cleanup Method 4. Cleanup of crude extracts from plant material by gel permeation chromatography on polystyrene gels
Cleanup Method 5. Cleanup of large quantities of fats for analysis of residues of organochlorine and organophosphorus compounds
Cleanup Method 6. Cleanup of crude extracts from plant and animal material by gel permeation chromatography on a polystyrene gel in an automated apparatus
Part 3: Individual Pesticide Residue Analytical Methods

Acephate, Methamidophos, 358-365
Aldicarb, 250
Captafol, 266
Captafol, 266-A
Captan, 12-A
Chlorthiophos, 465
Dalapon, 28
Dichlobenil, 225


X

Contents of Volume 1

Diclofop-methyl, 424
Ethylene Thiourea, 389
Folpet, 91-A
Heptenophos, 427
Metalaxyl, 517
Methomyl, 299
1-Naphthylacetic Acid, 434
Nitrofen, 340
Paraquat, 134-A
Pirimicarb, 309
Pirimiphos-methyl, 476
Pyrazophos, 328
Tetrachlorvinphos, 317
Triazophos, 401
Vinclozolin, 412
Part 4: Multiple Pesticide Residue Analytical Methods
Pesticides, Chemically Related Compounds and Metabolites Determinable by the Multiresidue
Methods (Table of Compounds)
S6
Substituted Phenyl Urea Herbicides
S 6-A Substituted Phenyl Urea Herbicides
S 7 Triazine Herbicides
S 8 Organohalogen, Organophosphorus and Triazine Compounds
S9
Organochlorine and Organophosphorus Pesticides
S 10 Organochlorine and Organophosphorus Pesticides
S 11 Potato Sprout Suppressants Propham and Chlorpropham
S 12 Organochlorine Pesticides
S 13 Organophosphorus Insecticides

S 14 Triazine Herbicides and Desalkyl Metabolites
S 15 Dithiocarbamate and Thiuram Disulphide Fungicides
S 16 Organophosphorus Pesticides with Thioether Groups
S 17 Organophosphorus Insecticides
S 18 Bromine-Containing Fumigants
S 19 Organochlorine, Organophosphorus, Nitrogen-Containing and Other Pesticides
S 20 Phthalimide Fungicides (Captafol, Captan, Folpet)
S 21 Ethylene and Propylene Bisdithiocarbamate Fungicides
Indexes
Index of Determinable Pesticides, Metabolites and Related Compounds (Index of Compounds)
Index of Analytical Materials
List of Suppliers Referenced in the Text-Matter of the Manual
Author Index


Senate Commission for Pesticides,
Deutsche Forschungsgemeinschaft
Members

Prof. Dr. Rudolf HeitefuB
(Chairman from 1987 to
1989)

Institut ftir Pflanzenpathologie und Pflanzenschutz der
Universitat
GrisebachstraBe 6, D-3400 Gottingen-Weende

Prof. Dr. Horst Borner

Institut fur Phytopathologie der Universitat

OlshausenstraBe 40/60, D-2300 Kiel

Dr. Dietrich Eichler

Shell Forschung GmbH
D-6501 Schwabenheim

Dr. Helmut Frehse

Bayer AG, PF-A/CE-RA,
Pflanzenschutzzentrum Monheim
D-5090 Leverkusen-Bayerwerk

Dr.-Ing. Siegbert Gorbach

Hoechst AG, Analytisches Laboratorium,
Pflanzenschutz-Analyse, G 864
Postfach 800320, D-6230 Frankfurt 80

Prof. Dr. Friedrich GroBmann

Institut ftir Phytomedizin der Universitat Hohenheim
Otto-Sander-Stral3e 5, D-7000 Stuttgart 70

Prof. Dr. Hans-Jurgen Hapke

Institut ftir Pharmakologie der Tierarztlichen Hochschule
Bischofsholer Darnm 15, D-3000 Hannover 1

Dr. Manfred Herbst

Asta Pharma AG
WeismtillerstraBe 45, D-6230 Frankfurt 1

Dr. Giinther Hermann

Bayer AG, PF-A/CE-Okobiologie,
Pflanzenschutzzentrum Monheim
D-5090 Leverkusen-Bayerwerk

Dr. Wolf-Dieter Hormann

Division Agrochemie der CIBA-GEIGY AG
CH-4002 Basel/Schweiz

Dr. Hans Th. Hofmann

Lorscher StraBe 10, D-6700 Ludwigshafen

Dr. Horst Hollander

Hoechst AG, Toxikologie-Gewerbetoxikologie
Postfach 800320, D-6230 Frankfurt 80

Prof. Dr. Georg Kimmerle

Bayer AG, Institut ftir Toxikologie
Friedrich-Ebert-StraBe 217, D-5600 Wuppertal 1

Dr. Jochen Kirchhoff

Institut ftir Phytomedizin der Universitat Hohenheim
Otto-Sander-StraBe 5, D-7000 Stuttgart 70


XII

Senate Commission for Pesticides

Prof. Dr. Fred Klingauf

Biologische Bundesanstalt fur Land- und Forstwirtschaft
Messeweg 11-12, D-33OO Braunschweig

Dr. Claus Klotzsche

Bruelweg 36, CH-4147 Aesch/Schweiz

Prof. Dr. Werner Koch

Institut fur Pflanzenproduktion in den Tropen und
Subtropen der Universitat Hohenheim
Kirchnerstrafle 5, D-7000 Stuttgart 70

Prof. Dr. Ulrich Mohr

Abteilung fur experimentelle Pathologie der
Med. Hochschule
Konstanty-Gutschow-Strafle 8, D-3000 Hannover 61

Prof. Dr. Friedrich-Karl
Ohnesorge

Institut fur Toxikologie der Universitat
Moorenstrafk 5, D-4000 Dusseldorf 1

Prof. Dr. Christian Schlatter

Institut fur Toxikologie der ETH und Universitat Zurich
Schorenstrafle 16, CH-8603 Schwerzenbach/Schweiz

Prof. Dr. Heinz Schmutterer

Institut fiir Phytopathologie und
angewandte Entomologie der Universitat
Ludwigstrafk 23, D-6300 Gieften

Prof. Dr. Fritz Schonbeck

Institut fiir Pflanzenkrankheiten und Pflanzenschutz der
Universitat
Herrenhauser Strafie 2, D-3000 Hannover 21

Prof. Dr. Fidelis Selenka

Institut fiir Hygiene der Ruhr-Universitat
Postfach 102148, D-4630 Bochum

Prof. Dr. Hans-Peter Thier

Institut fiir Lebensmittelchemie der Universitat
Piusallee 7, D-4400 Miinster

Dr. Ludwig Weil

Institut fiir Wasserchemie und Chemische Balneologie
der Technischen Universitat
Marchioninistrafie 17, D-8000 Miinchen 70

Prof. Dr. Heinrich Carl Weltzien Institut fiir Pflanzenkrankheiten der Universitat
Nuflallee 9, D-5300 Bonn 1

Permanent Guests
Prof. Dr. Fritz Herzel

Bundesgesundheitsamt
Postfach 330013, D-1000 Berlin 33

Prof. Dr. Alfred-G. Hildebrandt

Institut fiir Arzneimittel des Bundesgesundheitsamtes
Postfach 330013, D-1000 Berlin 33


Senate Commission for Pesticides

XIII

Secretaries of the Senate Commission for Pesticides
Frau Dr. Dagmar Weil

until 1986

Institut fur Wasserchemie und Chemische Balneologie
der Technischen Universitat
Marchioninistrafie 17, D-8000 Munchen 70

Dr. Friedhelm Dopke
from 1987 to 1989

Institut fur Pflanzenpathologie und Pflanzenschutz
der Universitat
Grisebachstr. 6, D-3400 Gottingen-Weende

Assessor Wolfgang
Bretschneider t 1990

Deutsche Forschungsgemeinschaft
Kennedyallee 40, D-5300 Bonn 2



Working Group on Residue Analysis,
Senate Commission for Pesticides
Members and Guests

Dr. Hans-Gerd Nolting
Biologische Bundesanstalt fur Land- und Forstwirtschaft
(Chairman from 1988 to 1989) Messeweg 11-12, D-3300 Braunschweig
Prof. Dr. Hans-Peter Thier
Institut fur Lebensmittelchemie der Universitat

(Chairman from 1976 to 1988) Piusallee 7, D-4400 Munster
Prof. Dr. Hans Zeumer
t 1988
(Chairman from 1961 to 1976)
Dr. Gtinther Becker

Chemisches Untersuchungsamt
Charlottenstrafie 8, D-6600 Saarbrucken

Prof. Dr. Winfried Ebing

Biologische Bundesanstalt fur Land- und Forstwirtschaft
Konigin-Luise-Straite 19, D-1000 Berlin 33

Dr. Siegmund Ehrenstorfer

Landesuntersuchungsamt fur das Gesundheitswesen,
Fachabteilung Chemie
Fritz-Hintermayr-Strafle 3, D-8900 Augsburg

Dr. Dietrich Eichler

Shell Forschung GmbH
D-6501 Schwabenheim

Dr. Helmut Frehse

Bayer AG, PF-A/CE-RA,
Pflanzenschutzzentrum Monheim
D-5090 Leverkusen-Bayerwerk

Dr. Ing. Siegbert Gorbach

Hoechst AG, Analytisches Laboratorium,
Pflanzenschutz-Analyse, G 864
Postfach 800320, D-6230 Frankfurt 80

Prof. Dr. Fritz Herzel

Bundesgesundheitsamt
Postfach 330013, D-1000 Berlin 33

Dr. Wolf-Dieter Hormann

Division Agrochemie der CIBA-GEIGY AG
CH-4002 Basel/Schweiz

Prof. Dr. Antonius Kettrup

Fachbereich Chemie u. Chemietechnik der Universitat
Postfach 1621, D-4790 Paderborn

Dr. Jochen Kirchhoff

Institut fur Phytomedizin der Universitat Hohenheim
Otto-Sander-StraBe 5, D-7000 Stuttgart 70

Prof. Dr. Hans Maier-Bode

Tannenweg 7, D-7884 Rickenbach b. Sackingen

XVI

Working Group on Residue Analysis

Dr. Egon Mollhoff

Bayer AG, PF-A/CE-RA,
Pflanzenschutzzentrum Monheim
D-5090 Leverkusen-Bayerwerk

Dr. Ludwig Weil

Institut fur Wasserchemie und Chemische Balneologie
der Technischen Universitat
Marchioninistrafie 17, D-8000 Miinchen 70

Editorial Committee

Prof. Dr. Hans Zeumer t
(Former Chairman, until 1986)
Dr. Jochen Kirchhoff
(Present Chairman,
appointed in 1986)
Dr. Helmut Frehse
Dr. Hans-Gerd Nolting
Prof. Dr. Hans-Peter Thier

Parti
Introduction and Instructions



Derivation of the Limits of Detection and
Determination Applying the Calibration Curve
Concept
(German version published 1991)

1 Introduction
It is a familiar experience in trace analysis that analytical results can become uncertain or even
entirely unreliable if the substance to be analyzed (the analyte) is present in very low concentrations. This can be due to various causes which can also occur simultaneously, e. g.:
— Co-extractives from the matrix simulate the analyte, thus leading to blank values.
— The analyte is lost during the cleanup in varying proportions, so that the results from parallel analyses vary to an unacceptable extent.
— The minute amounts of the analyte are not, or are only inadequately substantiated by the
measuring system.
Consequently there are three categories in which an analytical result can fall:
A. The presence of the analyte is shown; a quantitative determination is possible.
B. The presence of the analyte can indeed still be shown, but a reliable quantitative determination is no longer possible.
C. The presence of the analyte can no longer be established with sufficient probability; the
analyte must, therefore, be considered as "not detectable".
Categories A and B are separated by the limit of determination (LDM), categories B and
C by the limit of detection (LDC).
For these reasons, a convention needs to be established on how to define LDM and LDC. *)
Both can be used in different respects:
1. By specifying LDM and/or LDC, the author of an analytical method can give other
analysts using the method an indication as to its performance.
2. The analyst can more accurately characterize his findings with the aid of LDM and/or
LDC, e.g. by presenting a result (in case B only!) as "Content of compound X in the

sample < [LDM]", or in case C, as "Compound X not detectable in the sample, LDC =
[LDC]". The letters in brackets denote the numerical value for either LDM or LDC; see
also p. 45, Vol. 1.

*) In the absence of a defined limit of determination, it may be expedient for the analyst to use the routine
limit of determination (RLDM; see p. 43, Vol. 1) as the reporting level, if the analytical problem permits such an approach. In this case, however, the analyst must clearly state that the RLDM was used
as the threshold when reporting the result of an analysis as " < ...", thus indicating that quantitation
below this level was not attempted and there is no evidence whether or not the analyte is determinable
when present in concentrations smaller than the RLDM.


4

Limits of Detection and Determination

Numerical values for LDM and LDC are valid only for each special case of the analyst's
instrumental and operating conditions. "Generally valid" statements such as "The method
has a LDM (LDC) of ..." are, therefore, not appropriate.
The pertinent literature contains numerous recommendations for a mathematical definition
of the LDC and/or LDM. Nevertheless, often even the nomenclature is not uniform. Frequently LDC and LDM are used as synonyms; additionally there are other, and sometimes
even incorrect terms in use, e.g. "sensitivity".
Older recommendations, in part still used today, relate the LDC or LDM to the blank value
or instrument noise and their random scatter (standard deviation). The measured signal may
then be considered to be significant if its mean value differs from the mean of the blank or
noise by a given multiple of the standard deviation. This kind of evaluation, however, is only
justified if the errors inherent in the measurement procedure are caused exclusively by the instrumental conditions, e.g. with photometric measurements after a wet ashing, or with
establishing a calibration curve from standard solutions in gas chromatography. It is,
therefore, not comprehensive enough for application in residue analysis.
The results of residue analyses are decisively affected by primary factors from the preceding
extraction and cleanup steps, such as variable "recoveries". For use in this Manual, therefore,

the derivation of the LDC and, from it, of the LDM, is based upon results obtained from complete analytical procedures. Moreover, the additional Requirements II and III were introduced
for the definition of the LDM. The LDM is defined as the smallest value for the content of
an analyte in an analytical sample that satisfies the three following requirements:
I The LDM is greater than, and significantly different from the LDC.
II The recovery (sensitivity) at the LDM is equal to, or greater than 70%.
Ill The coefficient of variation at the LDM, from replicate determinations, is equal to, or
smaller than 0.2 (equivalent to 20%).
The recommendation given in the Section on Limits of Detection and Determination on
pp. 37 ff, Vol. 1, still required the existence of blank values for estimating LDC and LDM.
However, it also demanded the requirement of the recoveries exceeding 70% to be checked (II)
by stepwise fortification and calculation of the regression line. In addition, the smallest fortification level had to meet Requirement III.
With the progress of analytical techniques, however, blank values often do not show any
more, or are not significant for the interpretation of an analytical result. In order to enable
a convention on the definition of the LDC and/or LDM in these cases, the calibration curve
concept (also familiar from many publications) is proposed here for application in residue
analysis. A special advantage of this concept is that the LDC can be determined with actually
measured values, and that neither authentic control samples nor blank values are required.
This concept will be presented and mathematically sustained. For its routine application
from a series of measurements, the use of a suitably programmed computer is recommended.
In individual cases, both limits can be derived graphically, with relatively little calculation
effort and with sufficient accuracy, from a plot of the calibration curve and its prediction interval. For an example, see 9.3.


Limits of Detection and Determination

5

2 Calibration curve concept
2.1 Basic considerations
The aim of the concept is to define the limit of detection and, resulting from it, the limit of

determination for the results obtained when a given analyte is determined with a particular
analytical method in an individual laboratory. The definition proceeds from the calibration
curve obtained with the analytical method and employs the upper and lower limits of the
prediction interval of the curve for deriving LDC and LDM. The prediction interval is used
here as the confidence interval.
The operation described for determining LDM permits an appropriate consideration of Requirement I. Requirement III is integrated into the formulae used to calculate LDM. Determining the slope of the calibration curve will check Requirement II.
2.2 Establishing the calibration curve
To obtain the calibration curve, a series of fortification experiments is run with k given levels

for which the corresponding signal values

are measured, with m, replicate experiments per level Xt. The number of replicate exit
periments may be different on each fortification level X{. In total, n = £ m^ value pairs
[ l
for X and Y will be obtained.
=
The given levels (X) of the analyte in the samples and the corresponding signal values (Y)
are connected by the method-specific calibration function, which will be linear — at least
locally — in good approximation. In this case, only few value pairs for X and Y from fortification experiments are required (see 3.3.1).
From the total of the n value pairs obtained, the calibration curve is established. It is
represented by the regression line which is calculated according to the least squares method.
The function equation of the regression line is
Y=A+BX
where
Y = measured signal value for the content X
X = content of the analyte in the sample
A = intercept on the signal axis at the point X = 0
B = slope of the regression line (sensitivity of the method)
The prerequisite to deriving LDC and LDM is a certain minimum value for the slope B of
the calibration curve (see 4.3). Fortification experiments which do not meet this requirement

are useless and must be repeated under improved and appropriate experimental conditions.


6

Limits of Detection and Determination

Next, the prediction interval is calculated which symmetrically envelopes the linear calibration curve (see Figure 1). The curves for the upper (Y + ) and lower (Y_) limits of the prediction interval define that interval in which future ("predicted") signal values for any content
X are to be expected at a selected level of statistical significance.

x=0

X = Concentration

Fig. 1. Calibration curve with upper and lower limits of the prediction interval. Intersection of the line
Y = Yo with the prediction interval and the calibration curve; intersection points = Xl5 X3, X2.
A = theoretical blank value.
The points (Y UP , YLO), where both curves Y + and Y_ intersect with the signal axis, indicate the confidence interval for signal values yielded by samples with a "nil" content. Note
that this range is extrapolated from the results of the fortification experiments and is not
derived from the measurement of blank values.
Each signal value Yo > YUP yields three possible points of intersection with the calibration
curve and the limits of its prediction interval. They correspond, respectively, to the values
Xj, X 3 and X 2 (Figure 1) and form the basis for further derivations. When the curvature of
both the upper and lower limits of the prediction interval is negligible, X 3 can be considered
the arithmetic mean of X{ and X 2 with good approximation. X 2 is corresponding to LDC*
(Figure 4) and X£ v (Figure 5).
Xj and X 2 can be calculated from the formulae IIa and l i b (see 6.6, see also 3.2).


Limits of Detection and Determination

3 Limit of detection (LDC)
3.1 Definition
The limit of detection is defined by the smallest content of the analyte in an analytical sample,
for which the particular analytical method yields signal values which differ, with a selected
level of significance a, from signal values obtained from samples with a "nil" content (blank
signal values).
The level of significance, a, can be arbitrarily chosen. In most cases, values of a between
5 and 1% will allow a sufficient margin of safety. In residue analyses, usually a level of
a = 5%, i.e. a confidence level of S = 1 - a = 95%, is chosen.
Based on the n results (X^Yj) from the fortification experiments and the given
significance level, a, the limit of detection for an analyte is derived from the calibration curve.
It is represented by the smallest value X L D C for which the confidence intervals of the corresponding signal value Y LDC and of the signal value for a "nil" content do not overlap
(Figure 2).

X=0

LDC

X = Concentration

Fig. 2. Definition of the limit of detection (LDC).

3.2 Decision rules
The limit of detection corresponds, on the linear calibration curve, to a signal value Y LDC .
For the interpretation of further measurements, this implies:
- When the measured signal value Y is smaller than Y LDC , the analyte is considered not
detectable.

Limits of Detection and Determination

8

— When the measured signal value Y is greater than YLDC, the analytical sample is assigned
a content of X = (Y - A)/B (see X3 in Figure 1). The confidence interval belonging to X
is equivalent to the range from X{ to X2 in Figure 1.
At the limit of detection, the probability for the false proof of detecting the analyte which
in reality is not present in the sample (error of the first kind) is just equivalent to the selected
a of 5%. This is illustrated in Figure 2: The distribution curves for the signal values A and
YLDC each overlap by 2.5 area percent, corresponding to a test with a = 5% (two-sided).
The error of the second kind (false negative result in spite of a real content of the analyte being
present in the sample) depends on the actual content present. For X > LDC (corresponding to
Y > YLDC), it is smaller than 50%, for X = LDC, it is exactly 50% (Figure 3), i. e. a signal value
Y > YLDC will be caused, with a probability greater than 50%, by an analyte content >0.

C/3
II

^ s ^

"LDC

V
A

_.

X=0

-

ki

LDC

^ -

Y=A+BX

X = Concentration

Fig. 3. Confidence interval of a result X at the point LDC with distribution curve (schematic illustration).

3.3 Determining the limit of detection
3.3.1 Establishing the calibration curve

For the fortification experiments, it is advantageous to use authentic control samples, if
available, but other comparable material can also be used provided it does not contain any
substances that would interfere with the analysis.
The fortification levels extend from the anticipated LDC into the expected working range.
Note that the prediction interval which envelopes the calibration curve is narrowest at the
point X. Therefore, by suitable experimental planning and by making use of experience
available, a higher degree of precision can be reached through choosing fortification levels in
the neighbourhood of the anticipated LDC.


Limits of Detection and Determination

9

For best reliability of LDC, more than 4 evenly spaced fortification levels should be used
(k > 4), each with several replicate derminations (up to m = 4). However, for economical
reasons it will often not be possible for this statistically required number of measurements to
be carried out. A substantial reason for this is certainly the fact that for a given analyte,
depending on the sample material, different values for LDC can result, so that an accordingly
great number of fortification experiments would be required.
In general, it will be sufficient to choose 4-5 different fortification levels if the experiments
are repeated at least once on each level. Note that it is beneficial to use fewer replicates on
a greater number of levels, rather than to carry out more repetitions on fewer levels. The
number of replicates may, however, be different on the individual levels. Moreover, increasing
the number of fortification levels can, if need be, render it feasible to check the adequacy of
the model assumption, e.g. linearity.
Although to the disadvantage of statistical precision, in practice it may often be unavoidable
to derive the LDC from only one single measurement per fortification level. In this case,
however, a minimum of 6-8 measured values is required.
Measured values are only valid for the calculations if they represent the results of complete
analyses. It would be malpractice, for example, to split an extract obtained from a sample into
halves and to analyze these two portions separately in order to get "two" measured values.
The performance of the measurement set-up must be thoroughly checked before the fortification experiments are undertaken. Only such instrumentation which is in good condition,
complies to the standards, and produces sensitive and reproducible signal values, will be
suitable for establishing the calibration curve. Note that the instruments often produce quite
different signal values for the same amount of the analyte if the analyses are not carried out
consecutively. The signals must not be evaluated if they exhibit a drift, or if their quality
declines due to other reasons. Moreover, the signal values must not be adversely affected by
co-extractives from the sample material.
Using a suitable programmed computer, the parameters of the linear calibration curve and
the two limits of the prediction interval can easily be calculated from the individual value pairs
X{,Y{. The curves are best drawn by a plotter. For illustration, Figure 6 shows a graph and
print-out generated by computer, using Example 1 (cf. 9.1). In Section 9.3, a description is

given on how to proceed without the aid of a computer.
3.3.2 Graphical derivation of LDC

In the graph obtained (Figure 2; cf. Figure 7), draw a straight line, parallel with the abscissa,
from the point of intersection, YUP, to the point where it intersects the lower limit of the
prediction interval. This point corresponds, on the abscissa, to the value of LDC, the limit
of detection (cf. 9.3). For computer calculation of LDC, see 6.6.

4 Limit of determination (LDM)
4.1 Definition
Residue analyses are frequently performed to monitor foodstuff for compliance with
established maximum residue limits. For this reason, both risks, namely erroneously to state
the content of a sample either as conforming to, or exceeding the maximum residue limit, must