CONTRIBUTORS TO VOLUME XLIII Joaquin Abidn Pesticide Residue Group, University of Almeria, Ctra Sacramento sin, 04120 L...
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CONTRIBUTORS TO VOLUME XLIII Joaquin Abidn Pesticide Residue Group, University of Almeria, Ctra Sacramento sin, 04120 La Canadade San Urbano,Almeria, Spain Ana Agiiera Pesticide Residues Group, University of Almeria, Ctra Sacramentos/n, 04120 La Canada de San Urbano, Almeria, Spain Lutz Alder FederalInstitute for Risk Assessment, Thieleallee 88-92, Berlin D-14195, Germany Michelangelo Anastassiades Stuttgart Regional Chemical and Veterinary Control Laboratory, Schaflandstrasse3/2, 70736 Fellbach, Germany Andre de Kok PesticidesAnalysis Group, VWA - Food and Consumer Product Safety Authority, Hoogte Kadijk 401, 1018 BKAmsterdam, The Netherlands Amadeo R. Ferndndez-Alba Pesticide Residue Group, University of Almeria, Ctra Sacramento s/n, 04120 La Canada de San Urbano, Almeria, Spain Amadeo R. FernAndez-Alba Pesticide Residue Research Group, University of Almeria, 04071 Almeria, Spain Imma Ferrer Pesticide Residue Group, University of Almeria, Ctra Sacramento s/n, 04120 La Caiada de San Urbano, Almeria, Spain Richard J. Fussell Central Science Laboratory, Departmentfor Food, Environment and Rural Affairs, Sand Hutton, York Y041 1LZ, UK Alan R.C. Hill Central Science Laboratory, Departmentfor Food, Environment and Rural Affairs, Sand Hutton, York Y041 1LZ, UK Silvia Lacorte Department of Environmental Chemistry, IIQAB-CSIC, Jordi Girona 18-26, 08034 Barcelona, Spain E. Michael Thurman Pesticide Residue Research Group, University of Almeria, Almeria, Spain Luis Martin Plaza EuropeanCommission. Health and ConsumerProtectionDirectionGeneral. Rue Froissart101, Bureau 6/86-1040 Bruxelles, Belgium vii
Contributors to Volume XLIII
Stewart L. Reynolds Central Science Laboratory, Sand Hutton, York YO41 ILZ, UK Ellen Scherbaum Stuttgart Regional Chemical and Veterinary Control Laboratory, Schaflandstrasse 3 / 2 , 70736 Fellbach, Germany Hans-Jiirgen Stan Institute of Food Chemistry, Technical University, Gustau-Meyer-Allee 25, 0-13355 Berlin, Germany James R. Startin Central Science Laboratory, Department for Food, Environment and Rural Affairs, Sand Hutton, York YO41 1LZ, U K Christoph von Holst European Commission, DG Joint Research Centre, Institute for Reference Materials and Measurements, B-2440 Geel, Belgium
WILSON AND WILSON'S COMPREHENSIVE ANALYTICAL CHEMISTRY VOLUMES IN THE SERIES Vol. IA
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Analytical Processes Gas Analysis Inorganic Qualitative Analysis Organic Qualitative Analysis Inorganic Gravimetric Analysis Inorganic Titrimetric Analysis Organic Quantitative Analysis Analytical Chemistry of the Elements Electrochemical Analysis Electrodeposition Potentiometric Titrations Conductometric Titrations High-Frequency Titrations Liquid Chromatography in Columns Gas Chromatography Ion Exchangers Distillation Paper and Thin Layer Chromatography Radiochemical Methods Nuclear Magnetic Resonance and Electron Spin Resonance Methods X-Ray Spectrometry Coulometric Analysis Elemental Analysis with Minute Sample Standards and Standardization Separation by Liquid Amalgams Vacuum Fusion Analysis of Gases in Metals Electroanalysis in Molten Salts Instrumentation for Spectroscopy Atomic Absorption and Fluorescence Spectroscopy Diffuse Reflectance Spectroscopy Emission Spectroscopy Analytical Microwave Spectroscopy Analytical Applications of Electron Microscopy Analytical Infrared Spectroscopy Thermal Methods in Analytical Chemistry Substoichiometric Analytical Methods Enzyme Electrodes in Analytical Chemistry Molecular Fluorescence Spectroscopy Photometric Titrations Analytical Applications of Interferometry Ultraviolet Photoelectron and Photoion Spectroscopy Auger Electron Spectroscopy Plasma Excitation in Spectrochemical Analysis Organic Spot Tests Analysis The History of Analytical Chemistry
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Volumes in the series Vol. XI
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The Application of Mathematical Statistics in Analytical Chemistry Mass Spectrometry Ion Selective Electrodes Thermal Analysis Part A. Simultaneous Thermoanalytical Examination by Means of the Derivatograph Part B. Biochemical and Clinical Applications of Thermometric and Thermal Analysis Part C. Emanation Thermal Analysis and other Radiometric Emanation Methods Part D. Thermophysical Properties of Solids Part E. Pulse Method of Measuring Thermophysical Parameters Analysis of Complex Hydrocarbons Part A. Separation Methods Part B. Group Analysis and Detailed Analysis Ion-Exchangers in Analytical Chemistry Methods of Organic Analysis Chemical Microscopy Thermomicroscopy of Organic Compounds Gas and Liquid Analysers Kinetic Methods in Chemical Analysis Application of Computers in Analytical Chemistry Analytical Visible and Ultraviolet Spectrometry Photometric Methods in Inorganic Trace Analysis New Developments in Conductometric and Oscillometric Analysis Titrimetric Analysis in Organic Solvents Analytical and Biomedical Applications of Ion-Selective Field-Effect Transistors Energy Dispersive X-Ray Fluorescence Analysis Preconcentration of Trace Elements Radionuclide X-Ray Fluorescence Analysis Voltammetry Analysis of Substances in the Gaseous Phase Chemiluminescence Immunoassay Spectrochemical Trace Analysis for Metals and Metalloids Surfactants in Analytical Chemistry Environmental Analytical Chemistry Elemental Speciation - New Approaches for Trace Element Analysis Discrete Sample Introduction Techniques for Inductively Coupled Plasma Mass Spectrometry Modern Fourier Transform Infrared Spectroscopy Chemical Test Methods of Analysis Sampling and Sample Preparation for Field and Laboratory Countercurrent Chromatography: The Support-Free liquid Stationary Phase Integrated Analytical Systems Analysis and Fate of Surfactants in the Aquatic Environment Sample Preparation for Trace Element Analysis Non-destructive Microanalysis of Cultural Heritage Materials
Series Editor's Preface Pesticides play an important role in many areas of science and industrial activity, ranging in scope from the production of pesticides and their formulations to their wide range of applications in agriculture, especially in tropical countries, the environment and domestic applications. After pesticide application the target compound may degrade and residues will remain not only in the plant, leaves or fruits but also in various environmental matrices, like water, soil or sediments. Pesticide analysis requires a comprehensive approach and for this reason it is very difficult to compile in a single book all the analytical methods applied to the great variety and complexity of pesticides used and found nowadays in the environment. This book, edited by my old friend and colleague Amadeo R. Ferndndez-Alba, offers a focussed approach and presents analytical methods for the trace determination of pesticides in food. It is a useful addition to the Comprehensive Analytical Chemistry series since there is an urgent need for such a book due to the the large number of analytical chemists working in this emerging field. Its 10 chapters are devoted to sample preparation techniques, chromatographic-mass spectrometric methods, including GC-MS and LC-MS protocols, and quality control and proficiency testing schemes. The content of the book should enable the analyst to solve most of the problems encountered in pesticide analysis, and be useful both for newcomers as well as analysts in expert food laboratories looking either for a multiresidue analysis or for a tailor-made determination of a specific pesticide. The various chapters on mass spectrometry should also be useful to gain an insight into the techniques that are now routinely used in pesticide analysis, partly due to the lower costs of the MS instruments and also to the recently developed instruments like time-of-flight or hybrid instruments, based on triple quadrupoles followed by other mass analysers like ion traps. As well as being an applied book covering the increasingly growing field of pesticide residue analysis in food, it also contains some fundamental information on the techniques that are used. Food laboratories are well organised around the world since exports and imports of fruits and vegetables are a key issue in most economies. For this reason laboratories in the food area should be aware of new developments for ensuring quality control of pesticide xix
Series Editor's Preface residues in the various food matrices. Harmonisation of the methods is a key element to avoid any economic losses and to be able to sell any food product in any part of the world. This book will be of great help to those trading in this global economic market, being a useful tool-box that should help the analyst avoid pitfalls and assure method harmonisation in pesticide food control laboratories. Overall, this book covers most of the aspects of pesticide analysis in food and I expect it to become a key reference in the community of pesticide residue specialists. Finally I would like to thank not only the editor but also the various authors, some of whom have been my co-workers for several years, for their contributions in compiling this excellent book on pesticides in food. D. Barcel6 June 2004
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Preface
Far from being a mature analytical field, the trace determination of pesticides* continues to be a target topic for analytical chemists working in research centres, government and universities. This is a consequence of (i) new compounds, based on new chemical structures, continually being introduced into the market, (ii) new regulations, which are becoming ever more restrictive concerning the maximum residue limits legally permitted in food, and (iii) an increasing social, economic and academic interest in food safety, which has important trade implications. As a consequence of the specific characteristics of pesticides (i.e. high number of compounds, extremely diverse physical and chemical properties, analysis levels per day for effective control, system robustness, analytical performance, etc.) chromatography-based techniques are clearly the main choice for the practitioner. Traditionally, the introduction of mass spectrometric analysers/detectors coupled to gas chromatography (GC) or liquid chromatography (LC) has received less attention in this field compared to others, such as the environment. This is probably a consequence of special difficulties with these types of matrices/analytes, the high cost of these systems and the difficulties present in routine operation. However, during the last few years this situation has completely changed and chromatography-mass spectrometry (GC and LC) based techniques have become the core of pesticide food analysis. This change has been a result of important developments in and improvements of these techniques, making the great majority of pesticides/levels/commodities amenable to mass spectrometric detection with adequate analytical performance and robustness. In addition, we must not consider the detection step as separate from other stages of the analytical methodology, especially sample treatment and clean-up, which are closely-linked and together determine the quality and performance of the analyses as a whole. Therefore, developments in these *Note: The term "pesticide" covers a very diverse range of substances, not only single chemicals of natural or synthetic origin but additionally, among other things, micro-organisms. Throughout this text, the word "pesticide" is typically used in the restricted sense of a synthetic organic molecule and its degradation products.
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Preface areas have also contributed to improvements in pesticide food analysis and, in many cases, to the MS-based method itself. As far as pesticide residues are concerned, consumer confidence, food trade decisions and regulatory controls depend heavily on the quality of analysis. Thus, laboratories analysing food samples for the determination of pesticide residues need to be assured of the quality of their data and whether they are appropriate. The "fit-for-purpose" quality requirements are obviously related to the analytical procedures applied, as well as the legislative driving forces. Therefore, these topics are always relevant to get an adequate and realistic perspective of the proposed food analytical methods. On account of all the points mentioned above, the core of this book contains four chapters (chapters 6-9) devoted to chromatography-mass spectrometry methods. This part draws a clear and concise pathway between the relevant analytical aspects, allowing the reader to understand the analytical basis, technical characteristics and possibilities to evaluate pesticides in food by GC-MS and LC-MS. Furthermore, the book also gives a well-defined and critical compilation of the sample treatment and clean-up procedures, as well as injection techniques applied in GC and LC food analysis (chapters 3-5). Finally the book deals with aspects related to analytical quality control requirements for pesticide residues, in addition to the pesticide regulation aspects, which allows laboratories involved in residue analyses to meet the requirements of a recognised accreditation scheme (chapters 1, 2 and 10). These issues are considered in order to give to the readers a "field" dimension with regard to the proposed analytical tools. I give my heartfelt thanks to the authors who have contributed their expertise here. I must especially thank those authors who prepared their manuscripts early on, for their patience, while they waited for us to tidy up the remainder. I am impressed by the energy and work expended by all the authors and I hope they feel wellrewarded when seeing the final product. I would also like to thank Dr. Damia Barcel6 (Series Editor) for his help and support throughout this time. Amadeo Ferndndez-Alba
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Chapter 1
Quality control for pesticide residues analysis Alan R.C. Hill, James R. Startin and Richard J. Fussell
1.1 INTRODUCTION The determination of pesticide residues presents analysts with challenges ranging from moderately to extremely difficult. Some of the complexities and problems are sufficiently subtle, or lacking robust solutions, that it has always been uncomfortably easy to generate spurious results. The term "pesticide" has a very diverse range of meanings in terms of biological activity but it also encompasses many hundreds of chemicals, exhibiting extremely diverse physical and chemical properties. Consequently the analytical methods involved are also diverse, although the majority of pesticides are amenable to mass spectrometric detection. Amongst the most problematic for the analyst are those pesticides that are labile, or volatile, or have no chemical or physical features that differentiate them from co-extractives, or are zwitterionic, or are insoluble in anything, or are of incompletely-defined structure. Such analytes tend to require so-called single residues methods (SRMs) and therefore the cost per result of analysis tends to be very high. In contrast, certain large groups of pesticides share physico-chemical properties that render them amenable to the use of multiresidue methods (MRMs). Some MRMs are capable of detecting the presence of several hundred pesticides as a part of a single determination, whereas others are intended for a much smaller group, so that "typical" MRMs and SRMs represent the extremes of a continuum. Mass spectrometry (MS) coupled with gas or liquid chromatographic separation, and certain techniques based on detection of a common moiety, are particularly suited for use with MRMs. However, MRMs can provide special challenges for analytical quality control (AQC). Comprehensive Analytical Chemistry XLIII FernAndez-Alba (Ed.) © 2005 Elsevier B.V. All rights reserved
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A.R.C. Hill, J.R. Startin and R.J. Fussell Almost by definition, pesticides are toxic to something and therefore present risks-to consumers, the environment or whatever-which require control. Because of their potential for biological impact and the consequential need for a precautionary approach, the limits at which residues must be controlled in food and other matrices are low-from sub-pg/kg to mg/kg. The matrices in which residues may occur is extremely diverse, ranging from reasonably homogeneous liquids (water, beverages, oils, emulsified fats, etc.) to highly heterogeneous solids (animal tissues, fruit, vegetables, etc.). Whatever techniques are used in residues analysis, a sound knowledge of the operating principles of the method and equipment will invariably help to resolve problems arising during the use of the method and help to select the most appropriate AQC procedures. During the initial development of an analytical method, the analyst will gain insights into its strengths and weaknesses, and the factors critical to producing acceptable results can be identified though ruggedness testing [1]. This chapter does not address method development but key indicators of method performance should be identified at that stage, with a view to defining AQC requirements. As far as pesticide residues are concerned, consumer confidence, food trade decisions and regulatory controls depend heavily on the quality of analyses. Analytical mistakes can be extremely costly in terms of lost trade, destruction of crops, fines for growers, litigation against the analyst, and so on. AQC must therefore be rigorous but the challenging nature of the analyses creates conflicting requirements. The cost of the residues analysis is generally rather high, few of the techniques are rapid, and AQC requirements can contribute substantially to costs and time requirements. High costs and lengthy analyses constrain the numbers of samples analysed but, residues being generally very variable in distribution, most clients would prefer more data in order to ensure satisfactory control of residues. Thus, there is an inevitable desire to limit the cost of AQC, because its benefits are not as immediately tangible as the results produced from the clients' samples. However, good AQC can avoid expensive, and potentially very damaging, mistakes and the analyst and client must recognise the risks associated with inadequate AQC. The AQC procedures adopted must balance the competing requirements for sufficient numbers of results, affordable costs and sufficient reliability, such that the information generated is fit for its purpose. Reliability has two aspects: identity and quantity (i.e., concentration) of the analyte. Identity is critical to all pesticide residues analysis. There can be no such thing as a determination of "pesticides" as a residue and, in those few cases where it is possible to integrate the response of groups of pesticides into a simultaneous determination, the data are unlikely to be fit for anything more than crude 2
Quality control for pesticide residues analysis screening purposes. Determination of identity ranges from straightforward to difficult, because of the varying nature of the analytes. Inevitably, the lower the concentration the more difficult and expensive the confirmation of identity becomes. Determination of quantity can also be divided into two aspects: determination of whether or not a specific concentration limit has been exceeded and determination of the absolute concentration. For legal and trading purposes, pesticide residues in foods are controlled by maximum residue limits (or levels) (MRLs) and the routine AQC requirements for determining compliance with MRLs can be less stringent than where the "exact" concentration is to be determined. Checking for compliance with MRLs is an important tool for post-registration control of pesticides, ensuring that users adhere to good agricultural practice (GAP), i.e., that they adhere to the label recommendations approved at the time the pesticide was registered. Determination of the exact concentration is much more important for calculation of consumer intake of pesticides and for the consequential risk assessments made in respect of pesticides. Except in some relatively homogeneous materials, such as liquids and finely divided manufactured products, a consistent characteristic of pesticide residues is their heterogeneity of distribution within treated or contaminated crops, animals, the environment, etc. The term concentration is therefore usually taken to mean the average concentration in the sample received at the laboratory (laboratory sample). In some cases the distribution of residues within the laboratory sample, and especially within the units (e.g., individual fruit, vegetables) of the sample, may also be extremely heterogeneous. The average result obtained for the sample may or may not be representative of the whole population of material from which the sample was taken. Sampling protocols, such as that of Codex [2], are intended to provide representative samples but, because it is virtually impossible to prove this in practice, MRLs usually apply to the laboratory sample. Analytical results are estimates of the true concentration (which cannot be known with complete certainty) and are inherently prone to measurement errors. The objective of AQC is to provide reassurance of fitness for purpose of, and appropriate data to support, the estimates (results) generated. Adherence to sound AQC procedures goes a long way towards ensuring mutual acceptance of laboratory results. This is of great importance in ensuring the free flow of trade between and within countries and indirectly supports the safe and efficient use of pesticides. The possible use of MRLs as non-tariff trade barriers is beyond the scope of this chapter but there is no doubt that confidence between trading partners in the residues data
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A.R.C. Hill, J.R. Startin and R.J. Fussell they produce serves to remove what could otherwise be prejudicial barriers to free trade. General aspects of AQC in trace analysis have been considered by Sargent [31 and Wells [41 but they do not focus on issues of special relevance to the determination of pesticide residues, especially in fresh commodities. Validation of methods for pesticide residues analysis has been considered by Hill and Reynolds [5] and comprehensively by many authors in a recent book by Fajgelj and Ambrus [6]. AQC requirements for pesticide residues analysis have also been dealt with comprehensively by the European Union (EU) [7]. This chapter is based upon the EU requirements, because they have been adopted, in part or in whole, in well over 100 residues laboratories in some 20 European countries. They have also been adopted or adapted, in part, in some other parts of the world. Some examples are provided to show the practice and limitations of the quality control procedures described. We use the term "analyte" to denote the chemical species present at the start of the analysis and/or the species that enters the detector. The analyte present at the start may differ from the analyte detected but, in each case, these are expected to be qualitatively and quantitatively related to one another. The analyte may be the pesticide, its target degradation or derivatisation products, or the internal standard. The term "matrix" (plural matrices) is used to denote the sample type, or its extract at any stage of the analysis. Thus "apple matrix" may be anything from whole apples to an aliquot of a cleaned-up extract. We use the term "lot" in the sense of Codex [2], to mean the bulk of material from which the laboratory sample originated. We use the term "sample" to mean the laboratory sample (i.e., that received for analysis), the analytical sample (the laboratory sample after preparation and processing for sub-sampling), or the blank/reference samples used for quality control purposes. We use the term "test portion" to denote the sub-sample analysed and the term "extract" to denote extracted solutions, volatiles or residual solids from solutions produced from the test portion, irrespective of clean-up.
1.2 ACCREDITATION In many countries of the world, it is now mandatory that residue laboratory operations should meet the requirements of a recognised accreditation scheme, usually requiring compliance with the requirements of ISO 17025. Many countries have recognised the need for accreditation and the requirements of global trade are leading to others following suit. Whilst certain requirements of accreditation schemes may seem a little excessive or impractical for 4
Quality control for pesticide residues analysis the residues laboratory, accreditation has been a powerful driving force in the implementation of improved quality standards. The documentation required may also seem onerous in some cases, and there may be scope for improving efficiency in this respect, but even the best laboratories now possess better evidence of the quality of their data than they did in the past. An important aspect of accreditation documentation is the use of standard operating procedures (SOPs), which describe the principles of the work and how it is to be performed. In the early days of accreditation of residues analysis there was a strong emphasis on the accreditation of specific methods for specific tasks. The problem with such an approach is that every extension of scope of the method-to a new concentration, to a new sample matrix, or to a new analyte in the case of MRMs-requires extensive validation before any samples are analysed. In many cases, this is either too time-consuming or too costly to be practicable. For this reason, there is a growing emphasis on the use of so-called "generic" accreditation, where the use. of the technique is accredited and the supporting validation is produced by adherence to performance criteria adopted as part of the accreditation. For example, in our laboratory, generic accreditation to the ISO 17025 standard has been implemented for HPLC-MS or HPLC-MS/MS confirmation of the presence (identity), demonstration of absence (subject to a reporting limit), or determination of concentration of any amenable analyte in extracts. The SOP allows for variations in the calibration protocol and experimental conditions, but carefully specifies the minimum performance requirements for chromatography, MS, and quantitative determination. Whatever system of accreditation is adopted, sample data records, laboratory notebooks, chromatograms, tables of results, disks bearing chromatographic or spectral data, etc., must be stored in a safe place for subsequent scrutiny. The period of retention should be in accordance with national or accreditation requirements.
1.3 SAMPLING, TRANSPORT, PROCESSING AND STORAGE OF SAMPLES 1.3.1
Sampling
Here we refer to the practice of removing a sample from a bulk of some commodity, to be sent to the laboratory for analysis. We do not refer to the programme of sampling that may be devised to answer some specific question 5
A.R.C. Hill, J.R. Startin and R.J. Fussell or for general residue monitoring purposes. Sub-sampling to remove a representative analytical portion from the laboratory sample is dealt with in section 1.3.3. As indicated in section 1.1, pesticide residues are usually characterised by great variability in concentration within any population to be sampled. For example, Hill [8] and Hill and Reynolds [9] showed that the highest and lowest residues in the units of common fruit and vegetables usually differ considerably, in some cases by factors of several hundred. The situation is exacerbated by the common trading practice of mixing the produce from different growers, in order to produce larger and more uniform batches of product for large markets. Attempts to determine "typical" residue distributions in any particular commodity are probably doomed to failure, because of the almost endless range of scenarios that can affect the distribution. Although the distribution of residues in a bulk of a commodity (a lot) may be more or less random, it is impossible to be sure of this-with the possible exception of bulk liquids and manufactured products, which are usually well mixed. Most sampling recommendations for fruit, vegetable, cereal and animal primary products are based upon assembling samples incrementally from randomly chosen positions within the lot. Codex recommendations [2] are widely used throughout the world and recognise the possibility that the primary products can be sufficiently well mixed that, although a truly random distribution is not produced, the distribution may be such that a sample taken from a single position in the lot may be as representative as one taken from several positions. This is important because, in some cases, it may be physically or economically impracticable to increment samples from randomly chosen positions in the lot. For example, to take a truly random sample from a 1000-tonne standing lot of potatoes would not only take enormous time and effort, but it would also seriously jeopardise the quality of the remaining potatoes. The job is simplified if the potatoes form a moving stream on a conveyor belt but a truly random sample might still take far too much time, be too costly, or in some situations too hazardous to collect, to be practicable. Sampling is therefore a compromise between the aims, the cost and practicality. Cost and practicality are almost invariably the dominant considerations. 1.3.2
Laboratory sample transportation
Samples must be transported to the laboratory in clean containers and robust packaging. The costs of sampling and analysis can be wasted by poor practice at this stage. Polythene bags, ventilated if appropriate, are acceptable for 6
Quality control for pesticide residues analysis most samples but low-permeability bags (e.g., nylon-film) must be used for samples to be analysed for residues of fumigants. Generally, samples of commodities pre-packed for retail sale should not be removed from their packaging before transport. Very fragile or perishable products (e.g., ripe raspberries) may have to be frozen to avoid spoilage and then transported in "dry ice" or similar, to avoid thawing in transit. Samples that are frozen at the time of collection must be transported without thawing. Samples that may be damaged by chilling (e.g., bananas) must be protected from both high and low temperatures. Rapid transportation to the laboratory, preferably within a day or two, is essential for samples of most fresh products. In hot climates, refrigerated transport may be required, even for samples that are not frozen. The condition of samples delivered to the laboratory should approximate to that acceptable to a discerning purchaser, otherwise samples should normally be considered unfit for analysis. Samples must be identified clearly and indelibly, in a way that prevents inadvertent loss or confusion of labelling. The use of marker pens containing organic solvents should normally be avoided for labelling bags containing samples to be analysed for fumigant residues. 1.3.3
Sample preparation and processing prior to analysis
As in the case of sample transportation, the costs of sampling and, in some cases, the costs of analysis can be wasted by poor practice at this stage. On receipt, each laboratory sample must be allocated a unique reference code by the laboratory. Sample preparation should be in accordance with the definition of the commodity and the part(s) to be analysed, if MRL compliance is to be checked. Such definitions may be provided by national legislation or Codex [10] but these may vary according to the purpose of the work. For example, Codex recommendations are based on checking products in trade for compliance with MRLs (and hence GAP in the production of the products). Hence, the part(s) to be analysed may include inedible material, simply because residues on the sum total of edible and inedible parts were used to define the maximum residue that should result from GAP. In contrast, if the analysis is to estimate consumer exposure in, for example, a total diet study, the samples may be prepared for analysis by removing inedible parts, followed by cooking and mixing with other products. Sample preparation, sample processing and sub-sampling to obtain test portions must take place before the sample deteriorates visibly. Canned, dried 7
A.R.C. Hill, J.R. Startin and R.J. Fussell or similarly processed samples should normally be analysed within the stated shelf-life, unless stored in deep freeze. Sample processing and storage procedures should be demonstrated to have no significant effect on the residues present in the test sample [11,12]. Where labile residues could otherwise be lost, samples may be comminuted frozen (e.g., in the presence of "dry ice" [13]). Where comminution is known to affect residues (e.g., dithiocarbamates [14] or fumigants) and robust alternative procedures are not available, the test portion should consist of whole units of the commodity, or segments removed from large units. All analyses should be undertaken within the shortest time practicable, to minimise sample storage. Determination of very labile or volatile residues should be started, and procedures involving potential loss of the analyte completed, on the day of sample receipt. If a single test portion is unlikely to be representative of the sample, as may be the case where a segment is removed from a large fruit or vegetable, replicate portions should be analysed even if an initial determination appears to show the absence of measurable residues.
1.4 PESTICIDE STANDARDS, CALIBRATION SOLUTIONS AND SIMILAR 1.4.1
Identity and purity of standards
Standard materials of analytes ("pure", or reference, standards) should be of known purity. Such standards must be uniquely identified, the date of receipt recorded, and an expiry date allocated. After the expiry date, the "pure" standard may be retained until a newly allocated expiry date if its purity is shown to remain acceptable, otherwise it should be replaced. The relative purity of new and old "pure" standards may be determined by comparing the detector responses obtained from freshly-prepared dilutions. Inexplicable differences in apparent concentration or identity between old and new "pure" standards should be investigated. Ideally, the identity of "pure" standards should be checked if the analytes are new to the laboratory. At method development or during validation, the response detected must be shown to be due to the analyte, rather than to an impurity or artefact. A peculiar problem in the determination of residues of certain pesticides is that the analyte can degrade during extraction, clean-up or chromatography, to produce a product that normally occurs in residues but which is excluded from 8
Quality control for pesticide residues analysis the residue definition. In such cases, positive results must be confirmed using techniques that avoid this problem.l 1.4.2
Storage of reference standards
"Pure" standards should be stored according to the suppliers' instructions (where given), to minimise degradation. Generally, storage at low temperature (refrigerator or freezer) in the dark is satisfactory. The containers must be sealed to avoid entry of water, which is especially likely during equilibration to room temperature. If a "pure" standard changes visibly (for example, if the colour changes, if crystals change to a powder or liquify) during storage it must not be used without checking the purity, unless the change is simply due to freezing and melting. An example of a poor quality standard is presented in Fig. 1.1. A reference standard of bupirimate had originally been acceptable. However, it probably became contaminated by traces of condensed water during equilibration to room temperature, following storage in the freezer, and a high proportion of the analyte had degraded to products (probably including ethirimol) that were not transmitted by the gas chromatographic system. When compared with a fresh standard of high purity (A), the faulty standard (B) was shown to be < 10% purity. 1.4.3 Preparation, use and storage of stock and working standards Stock standards are the initial dilutions of the "pure" standard, whereas the working standards are further dilutions for use in calibration and for additions in measurement of recovery. Stock standards are commonly prepared for a single analyte, whereas working standards may contain more than one, particularly for use with MRMs. The preparation of stock and working standards (which may be solutions, dispersions or gaseous dilutions) from "pure" standards requires careful attention to detail. Any inaccuracy in their preparation may not be apparent from checks of calibration or recovery but will directly affect analytical bias. The identity and mass (or volume, for highly volatile compounds) of the 1 This requirement applies where the product of analytical degradation must be distinguished from the chemically identical metabolite in the sample, in order to determine the residue level according to the definition. For example, 4,4'-dichlorobenzophenone from dicofol, tetrahydrophthalimide from captan and captafol, phthalimide from folpet, 2-chlorobenzonitrile from clofentezine.
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A.R.C. Hill, J.R. Startin and R.J. Fussell Abundance 280000 260000 240000 220000 200000 180000 160000 140000 120000 100000 80000 60000 40000 20000 0 9.00
9.20
9.40
9.60 9.80 Retention time, min
10.00
10.20
10.40
Fig. 1.1. Chromatograms obtained from solutions of nominally the same concentration, prepared from two reference standards of bupirimate. (A) New reference standard; (B) old reference standard presumed to have been degraded by condensation formed during warming from storage at - 18C. reference standard, the identity of the solvent (or other diluent), and the volumes and dilution steps employed, must be recorded. The potential cost of illegible labels is very high, so stock and working standards must be labelled indelibly. It is usually impossible to record all necessary information on the flasks, etc., that contain working standards, so careful record keeping in a paper-based system or a computerised laboratory information management system (LIMS) is essential. At some stage in the data recording and calculation procedures, concentrations must be corrected for the purity of the reference material. This should be easy to arrange with a LIMS but it is easily overlooked. The analyte must not react with, and should have adequate solubility in, the solvent(s) used to prepare solutions. Polar analytes that are likely to degrade in protic solvents, such as methanol or water, may be dissolved in acetonitrile. Hydrolysis or oxidation is an ever-present threat to the stability of many standards. Maintenance of an appropriate pH or the use of an antioxidant may be required. Solvents which are prone to oxidation are usually 10
Quality control for pesticide residues analysis sold with a stabiliser or anti-oxidant but care is required if redistilled before use. In general, methanol should be avoided for dissolution of esters, because of the potential for transesterification, particularly under acidic conditions. Methanol also induces a rearrangement of iprodione. Higher alcohols may be less of a problem in both cases. In various solvents, pesticides such as pyrethroids (prone to epimerisation) and dicofol (prone to loss of chloroform) must be maintained under mildly acidic conditions, even in non-aqueous solvents. Analytes which can form tightly bound complexes (such as paraquat, glyphosate or thiram) may require maintenance of particular pH conditions, the addition of "competing" complexing agents, and/or the use of plastics instead of glassware. The solvent(s) must be appropriate to the method of analysis and be compatible with the determination system used. Even small proportions or quantities of inappropriate solvents may be detrimental to peak shape in chromatography or to the response of some GC detectors. If the analyte is known to be prone to photolysis, solutions should be kept in the dark as much as possible and certainly out of sunlight. Solutions of photolytically unstable analytes may require the use of darkened or shielded flasks and vials. Analytes that possess no UV chromophore are unlikely to undergo direct photolysis but it is better practice to keep all solutions in the dark when not in use. Unless suitably accurate facilities are available, not less than 5-10 mg of the "pure" standard should be weighed. Volatile liquid analytes should be dispensed by weight or volume (if the density is known) directly into solvent. Gaseous (fumigant) analytes may be dispensed by bubbling into solvent and weighing the mass transferred, or by preparing gaseous dilutions (e.g., with a gas-tight syringe, avoiding contact with reactive metals). Analyte solutions (or other dilutions) should be allocated an expiry date, after which they should normally be discarded. If practicable, newly prepared stock standards should be diluted and compared with those that have just expired. This has the dual benefits of checking against the possibility of weighing or dilution errors and of checking whether the expiry date is either unduly optimistic or pessimistic. If the average measured value for the new solution differs by more than ±+5% from the old one,2 the new solution should be checked for accuracy against a further newly prepared one. If the number of replicate determinations required to distinguish a difference of 5% is unacceptably large for problematic analytes, the acceptable range may be increased to ± 10%. If the old standard produces - 95 (or 90% in the case of 2 Alternatively, a t-test of the means should not show a significant difference at the 5% level.
11
A.R.C. Hill, J.R. Startin and R.J. Fussell problematic analytes) of the response obtained from the new standard, the storage period for solutions must be shortened or the storage conditions improved. If the responses from old and new standards do not differ significantly, a longer storage period may be considered. Aqueous suspensions of insoluble dithiocarbamates and solutions (or gaseous dilutions) of highly volatile fumigants must be prepared freshly. The concentration of such a standard may be checked only by comparison with a further one prepared independently. Solutions should be stored at low temperature, in a refrigerator or freezer, sealed to avoid loss of solvent and entry of water which may condense during warming to room temperature. Unless they are internally standardised, solutions must be equilibrated to room temperature and re-mixed before use. If solubility at low temperatures is limited, great care must be taken to ensure that the analyte is completely re-dissolved after storage of solutions. Unless they are internally standardised, solvent losses by evaporation from stock and working standard solutions (and extracts) are unacceptable. Solvent losses from small volumes are difficult to monitor and, in the absence of an internal standard, great care is required to avoid evaporation. Septum closures on auto-sampler vials are particularly prone to evaporation losses (in addition to being a source of contamination) and, if a solution/extract is to be retained, the vial cap should be replaced as soon as practicable after piercing the septum. 1.5 EXTRACTION AND CONCENTRATION
1.5.1
Extraction conditions and efficiency
Test portions should be disintegrated thoroughly during extraction to maximise extraction efficiency, except where this is known to be unnecessary (e.g., some SFE extractions) or inappropriate (e.g., for determination of fumigants or surface residues, or for the analysis of liquids). Temperature, pH, etc., must be controlled if these parameters affect extraction efficiency, analyte stability or solvent losses.
1.5.2
Extract concentration and dilution to volume
Great care must be exercised when extracts are evaporated to dryness, as trace quantities of many non-ionic analytes can be lost in this way, particularly if the clean-up has been very effective in removing co-extractives such as fatty materials. A small volume of high boiling point solvent may be added as a "keeper" but the evaporation temperature should normally be as 12
Quality control for pesticide residues analysis low as practicable. Frothing and vigorous boiling of extracts, or dispersion of droplets, must be avoided. A stream of dry nitrogen or vacuum centrifugal evaporation is generally preferable to the use of an air stream for small-scale evaporation, as the air is more likely to lead to oxidation or to introduce water and other contaminants. Where extracts are diluted to a fixed volume for external standardisation, accurately calibrated vessels of not less than 1 ml capacity should be used and further evaporation should avoided. Alternatively, an internal standard may be used, particularly for small volumes. Analyte stability in extracts should be investigated during method development or validation. Storage of extracts in a refrigerator or freezer will minimise degradation but potential losses at the higher temperatures of an autosampler rack should not be ignored. 1.6
1.6.1
CONTAMINATION, INTERFERENCE, AND NATURAL SOURCES OF THE ANALYTE Contamination
Samples must be kept separate from each other, and from other sources of potential cross-contamination, during transit to, and storage at, the laboratory. This is particularly important with surface or dusty residues, or with volatile analytes. Samples that are known, or thought, to bear such residues should be doubly sealed in polythene or nylon bags and transported and processed separately. Pest control near, or especially in, the laboratory should be restricted to the use of pesticides that will not be sought as residues. This is critically important for sample reception and preparation facilities. The otherwise acceptable use of household insecticides in food preparation facilities has unwittingly led to the contamination of samples being prepared for total diet studies in the UK and USA. Volumetric equipment, such as flasks, pipettes and syringes, must be cleaned scrupulously, especially for re-use. As far as practicable, separate glassware, etc., should be allocated to standards and extracts, in order to avoid cross-contamination. Badly scratched or etched glassware should be avoided. Solvents used for fumigant residues analysis should be checked to ensure that they do not contain the analyte. Where an internal standard is used, unintended contamination of extracts or analyte solutions with the internal standard, or vice versa, must be avoided. Contamination of samples and extracts (and possibly even standards) with the analyte derived from non-pesticide sources can be insidious. The use of 13
A.R.C. Hill, J.R. Startin and R.J. Fussell rubber materials that have been manufactured using dithiocarbamate vulcanisation accelerators must be avoided otherwise dithiocarbamates and/or ethylenethiouruea [15] may be detected as "pesticide residues". Similarly, the use of rubber vial seals in which diphenylamine has been incorporated as an anti-oxidant [15] may give rise to the detection of spurious "residues". 1.6.2
Interference
Not all interference originates from the samples. Equipment, containers, solvents (including water), reagents, filter aids, etc., should be checked as sources of possible interference. Rubber and plastic items (e.g., seals, protective gloves, wash bottles), polishes and lubricants are frequent sources. The plasticisers, monomers, polymerisation and cross-linking accelerators, UV-stabilisers, anti-oxidants, slips, etc., which can occur in and on such products can create serious problems. Perhaps the most ubiquitous of interferents in pesticide residues analysis are phthalates, silicones and long-chain hydrocarbons. These species are so common in buildings, furniture and even parts of analytical equipment that their presence should come as no surprise but the analyst should try to minimise the level of contamination and interference. Vial seals made of rubber materials should be PTFE-lined. Extracts should be kept out of contact with seals, especially after piercing, by keeping vials upright. Vial seals must be replaced quickly after piercing, if re-analysis of the extracts is necessary. Silicone rubber materials generally contain rather fewer interfering chemicals than other rubbers but, inevitably, they present a high risk of contamination with low molecular weight silicones. Analysis of reagent blanks should help to identify sources of interference in the equipment or materials used. Interference from co-extractives (i.e., natural constituents extracted from samples) is frequent in pesticide residues analysis. The interference may be peculiar to the determination system used, it may be variable in occurrence and intensity, and may also be subtle in nature. If the interference takes the form of a response overlapping that of the analyte, a different clean-up, chromatography or detector system may be required. Interference in the form of suppression or enhancement of detector system response is dealt with in section 1.7.3. If it is not practicable to eliminate the interference, or to compensate for it by matrix-matched calibration (section 1.7.3), the overall accuracy (bias) and precision of analysis should nonetheless comply with the criteria in section 1.8. 14
Quality control for pesticide residues analysis Interference can also occur between analytes in multi-residue analysis, where the use of mixed calibration standards is often essential (section 1.7.4). Ironically, the problem might be overlooked in MS determinations if analytes co-elute and produce common ions. Figure 1.2 shows an example of the determination of parathion-methyl in oranges, using GC-MS and electron ionisation (EI). The mixed calibration standard contained tolclofos-methyl that, under the GC conditions employed, co-eluted with parathion-methyl. Both pesticides produce a fragment ion at m/z 125, although this is of relatively low abundance in the spectrum of tolclofos-methyl. In the spectrum of parathion-methyl, the ions at m/z 125, 109 and 263 are of rather similar (and higher) abundance. In the example, it is clear that if the m/z 125 ion of the mixed standard solution is used to quantify the residue, an erroneous result will be obtained. A separate standard of parathion-methyl was used for correct calibration. 1.6.3
Natural sources of the analyte
Where the analyte occurs naturally in, or is produced from, samples, residues from pesticide use cannot be distinguished from natural levels. Examples are: inorganic bromide in all commodities; sulfur in soil, or samples contaminated with soil; carbon disulfide (CS 2) produced from cruciferous crops (Brassicaceae) and certain distantly related plants such as capers (Capparisspinosa). The last example only afflicts dithiocarbamate residue determinations based upon degradation to CS 2 but, as this is the most robust and cost-effective approach to this determination, it is used almost universally for the purpose. The natural occurrence of these various analytes must be considered in the interpretation of results, because low levels arising from the use of pesticides may be impossible to differentiate from those arising "naturally". There is no clear dividing line between "natural" levels and those arising from pesticide use, as both can give rise to highly variable concentrations. Although analysts may apply a "cut-off' concentration, below which "residues" are considered likely to be of natural origin, a proportion of incorrect decisions, above or below the cut-off concentration, is almost inevitable. 1.7 CALIBRATION AND CHROMATOGRAPHIC INTEGRATION 1.7.1
Mass calibration of mass spectrometric detectors
The software used in modern mass spectrometric detector systems display acquired spectra in a digitised form, disguising the fact that they are derived 15
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Quality control for pesticide residues analysis from an analogue signal. Good mass calibration is essential to ensure that the spectra acquired reflect the "true" mass spectra (and therefore identification against library spectra is acceptable) and to ensure that quantitative measurements are as reliable and sensitive as possible. 1.7.2
General requirements for quantitative calibration
Correct quantitative calibration is dependent upon correct identification of the analyte (see section 1.9). It is also dependent upon a good knowledge of the calibration function and dynamic range of the detection system. All detection systems can become saturated with high concentrations or quantities of analyte. It may be less obvious that all detection systems give a response similar to that of zero at some positive concentration or mass. Thus inclusion of a "zero" concentration or mass in the calibration curve should be treated with caution, because interpolation between the zero value and the next higher point in the curve may give a false impression of the lowest concentration or mass that can be detected. If it is essential to establish the lowest concentration or mass that can be detected, the system should be calibrated at and about the level at which it gives responses differing little from those produced by the zero level. At such concentrations, in addition to the inevitably decreased precision, calibration accuracy may also decline unless care is taken with the calculation of the calibration function. The concentration- or mass-response of all detection systems to an analyte tends to be variable, even over short periods of time, and the variation may be influenced by the material being analysed. In some cases, external standardisation may not be sufficient to reduce the impact of the variations or influences to an acceptably low level. In such cases, internal standardisation, particularly with stable isotope-labelled standards or the use of socalled standard addition, may be required. Standard addition is the addition of a known quantity of analyte to an extract (etc.) containing an unknown quantity of the same analyte. The difference in response produced is ascribed to the known quantity and the unknown quantity is calculated from its response. The term "internal standardisation" has different meanings and it is important to distinguish between them. (i) At its simplest, the internal standard is any suitable chemical, added to an extract prior to the final determination stage. Following detection, its function is to "correct" for uncontrolled changes in the volume of the extract, which is particularly useful where very small volumes of extracts are involved. The analyte: internal standard response ratio is calibrated routinely. (ii) An extension of 17
A.R.C. Hill, J.R. Startin and R.J. Fussell this procedure is to utilise an internal standard that shares most or all of the physico-chemical properties of the target analyte. The response ratio is then normally stable over time and need not be calibrated so frequently once this stability is demonstrated. Standard addition and isotopically labelled standards fall into this category and their response ratios can be expected to remain constant. (iii) Finally, the internal standard may be added to the test portion at the start of the analysis and the quantity of analyte is determined from the response ratio. Again, the response ratio is assumed to be constant but this approach to internal standardisation provides both calibration and an automatic correction for recovery (section 1.8). Bracketing calibration (i.e., quantitative calibration of the detector system immediately before and after the determination of residues in the samples) should be used unless the determination system has been shown to be free from significant drift in absolute response or response ratio, depending on the form of standardisation employed. In general, HPLC with UV-absorption detection shows slow and small drift, whereas some forms of liquid chromatography-mass spectroscopy (LC-MS) detection can give rapid and high drift. Detector responses used to quantify residues must be within the dynamic range of the system. Beyond either end of the dynamic range of the detector, analyte concentrations can only be quantified loosely. For example, less than or greater than x mg/kg. Certain detection systems, such as the flamephotometric detector operated in the sulphur mode and enzyme-linked immunosorbent assay are associated with non-linear responses, so that care is required to ensure that determinations are made within the dynamic range. LC-MS techniques also have a tendency to produce a response that is not wholly linear so, again, care is required to ensure operation within the dynamic range. In chromatographic analysis, especially GC, it is common to observe that the detector response, relative to the concentration or mass, declines more markedly as the level at which the analyte produces no signal is approached. This is another reason why "zero" points on the calibration curve should be treated cautiously. The detection system should be calibrated for every batch of analyses. If calibration for all analytes sought implies an unacceptably large number of calibration determinations, the system may be calibrated with representative analytes during each batch of analyses. A representative analyte is one that can be considered to represent a group of analytes by virtue of its physicochemical properties, its likelihood of occurrence in residues and/or, especially, its relatively extreme uncertainty of measurement. A suggested minimum 18
Quality control for pesticide residues analysis TABLE 1.1 Frequencies for calibration and recovery determination Representative analytes
Represented analytes
Frequency of calibration and recovery
Each batch
Detected response required Measurement required
Each batch Each batch
Either a rolling programme, to include all represented analytes intermittently, or all included in each batch Each batcha Only when residues are detected
"The result for the analyte is essentially qualitative, i.e., "present/not present lowest calibrated level" (LCL).
frequency for calibration of representative and represented analytes (i.e., the others in the group) is given in Table 1.1. Reliance on a rolling programme of representative analytes carries an increased risk of false negative results. Therefore representative analytes must be chosen very carefully and, if possible, it is better to institute a programme in which recovery of all analytes is assessed qualitatively (present/not present) in each batch. If a rolling programme (Table 1.1) of recovery and calibration of a represented analyte produces an unacceptable result, all results produced after the previous successful recovery or calibration of that analyte must be treated as potentially false negatives. The lowest calibrated level (LCL) is the lowest concentration with which the detection system is successfully calibrated for the batch. Residues detected below LCL should be considered poorly calibrated, and therefore normally reported as 20% (or > 30% at < 2 x LCL, if the LCL is close to the LOD). In cases where the MRL is approached or exceeded, these maximum drift values should be 10 and 15%, respectively. If the drift exceeds these values the determinations should be repeated, except where the extracts clearly do not contain the analyte(s) - LCL and the LCL response remains measurable throughout the batch. As indicated in the paragraph dealing with the assignment of the LCL, the limits for acceptability of calibration may be disregarded for special projects, 20
Quality control for pesticide residues analysis such as large-scale screening where the accuracy of individual results is relatively unimportant. 1.7.3
Matrix effects and matrix-matched calibration
Chemicals (usually of natural origin) present in samples can influence the measurement analyte of concentrations without being detectable as interference. The magnitude of the influence can range from major to trivial but the effects are notoriously variable in occurrence and intensity. Some techniques are particularly prone to them and others are inherently less likely to be affected. Headspace partitions are frequently influenced by the nature of the sample matrix, because of increased (rarely decreased) analyte affinity for the liquid/solid phase and, of course, this is not a function of the detection system used. In general, therefore, the matrix suppresses the measured value, compared with a calibration prepared with the reagents only. The differences in the degree of effect between different types of matrix can be enormous. The differences between samples of a single matrix type are usually less but can vary according to the lipid content, for example. Gas chromatograph injectors can provide increased (occasionally decreased) transmission of analytes in the presence of certain co-extractives. The consequential apparent enhancement of the detector response is usually ascribed to a "protective effect", inhibiting losses of the analyte that would otherwise occur during injection [16,17]. Matrix effects have been attributed variously to organic acids, polyols, etc., and it may be that the range of coextractives capable of producing an effect is partly dependent upon the instrument design, materials and operating conditions. These transient effects are usually distinct from, but presumably related in some ways to, so-called priming effects in gas chromatography. "Priming" is still frequently practiced in gas chromatography as it is often observed that analyte responses are relatively low prior to injection of some poorly cleaned-up extract. The nature of the detector itself, whether mass spectrometric or otherwise, does not usually play a significant part in these effects. The differences in the degree of enhancement effect between different types of matrix are usually relatively small but the differences between samples of a single matrix type can be almost as large as those between matrices. Atmospheric pressure ionisation (API) interfaces used in LC-MS are also prone to matrix effects but, in this case, the influence is most commonly a suppression of the detector response. This is due to co-elution of co-extractives, which compete with the analyte molecules for available charge
21
A.R.C. Hill, J.R. Startin and R.J. Fussell or, in the case of electrospray, for occupancy of droplet surfaces and therefore change the proportion of analyte molecules that generate observable ions. This kind of effect is restricted to LC-MS and LC-MS/MS. Suppression of the analyte signal is rarely total but it can frequently be sufficient to render a lowlevel residue immeasurable, or, if uncorrected, an exceedance of an MRL to appear to be a compliance. The differences in the degree of effect between different types of matrix can be large, as can the differences between samples of a single matrix type. Especially subtle problems may be associated with the use of positive-ion electrospray LC-MS. The technique is mainly associated with observation of ions generated by protonation of molecules ([M + HI+), but differently cationised molecules such as [M + NH4]+ and [M + Na] + also occur and, for some compounds, the ratio of the abundances of these different ions may be highly dependent on the Na+ concentration, solvent composition and coeluting compounds derived from the sample matrix. In our experience, aldicarb sulphoxide provides an example of a compound exhibiting such variability (Fig. 1.3), whereas the ratios exhibited by aldicarb (sulphide) and aldicarb sulphone are less prone to perturbation. Such changes can strongly affect the accuracy of measurement if this is based on a single cationised form.
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Quality control for pesticide residues analysis In contrast with the above examples, liquid chromatography with UVabsorption detection (LC-UV) is very unlikely to suffer from "hidden" matrix effects, because neither the transmission nor the extinction coefficient of the analyte is likely to be changed. Any interference by UV absorption is directly apparent. Matrix effects can be produced in UV-fluorescence detection, by quenching effects, but may be rendered more obvious if the UV absorption is monitored simultaneously. "Matrix-matched" calibration is one way to try to minimise the quantitative errors induced by matrix effects. The detection system is calibrated with known quantities of analyte added to suitable blank extracts (or test portions for headspace analysis). This is technically very simple, and can be very effective in some cases, but it does increase the costs of calibration. Costs and practicality become important considerations if batches of analyses incorporate many different types of matrix or if suitable blank samples are not readily available. If the matrix effects are minor or predictable, it may be acceptable to calibrate without matrix-matching, or to calibrate using a single matrix to represent all matrices analysed in the batch. This approach involves some risk of erroneous calibration and, in cases where the effects are major and/or unpredictable, the best ways to eliminate matrix effects are to calibrate either by standard addition or with an isotopically labelled internal standard. 1.7.4
Effects of pesticide mixtures on calibration
Calibration in multi-residue analysis, using mixed analyte solutions should be checked at method validation for similarity of detector response to that obtained from the separate analytes. If the responses differ significantly, or in cases of doubt, residues must be quantified using individual calibration standards in matrix or, better still, by standard addition. As indicated in section 1.6.2, interference between analytes may also influence calibration. 1.7.5 Calibration for pesticides that are mixtures of isomers or other components Where a pesticide is a mixture of isomers, detector response is usually assumed to be similar, on a molar basis, for each component. However, enzyme assays, immuno-assays and other assays with a biological basis may give calibration errors if the component ratio of the standard differs significantly from that of the measured residue. An alternative detection system should be used to quantify residues. In those cases where the response of a more 23
A.R.C. Hill, J.R. Startin and R.J. Fussell conventional detector to isomers differs, 3 separate calibration standards must be used. If separate standards are not available for this purpose, an alternative detection system should be used to quantify residues. 1.7.6
Calibration using derivatives or degradation products
Where the analyte is determined as a degradation product or derivative, the calibration solutions should be prepared from a "pure" standard of that degradation product or derivative, if available. Procedural standards may be used if they are the only practical option. 1.7.7 Chromatographic data acquisition rate, noise and integration Data acquisition rates can affect the uncertainty of measurement and it is important that this parameter is set correctly. If the acquisition rate is too slow, the apex of a chromatographic peak may be missed, the peak shape may appear incorrect and the integration of either peak height or area may be inaccurate. If the acquisition rate is too fast, the signal-to-noise ratio (S/N) may be too low for good integration. Calibration responses and those from extracts are affected similarly, compounding the uncertainty. Data are effectively averaged (bunched or acquired over a time period) by the acquisition software and this may or may not be under the full control of the analyst. The acquired data may also be additionally smoothed by the software, though this is usually under the control of the analyst. S/N data produced by either the software or the analyst are therefore often quite difficult to interpret. As long as S/N is measured consistently, some minimum value can be used as a criterion for determining the acceptability of instrument performance. But the same minimum value may not be appropriate for different instruments or for different operating conditions (and therefore in different laboratories). A further complication in the determination of S/N is the nature of the noise. Relative to the chromatographic (or mass) peak width, high frequency noise is reasonably easy to deal with. Low frequency, irregular noise is more difficult, not just for the determination of S/N but also for integration. "Chemical noise" (i.e., interference) is particularly problematic especially where additional clean-up or improved separation strategies are not 3 For example, the differing electron-capture efficiency of HCH isomers in ECD, or the differing
proton affinity of abamectin isomers in electrospray ionisation.
24
Quality control for pesticide residues analysis practicable. An experienced analyst may be able to provide a good estimate but there is no foolproof way of generating "correct" results under these circumstances. Chromatograms must be examined by the analyst and the baseline fitting checked and adjusted, as required. Where interfering or tailing peaks are present, a consistent approach must be adopted for the positioning of the baseline. Peak height or peak area data may be used, whichever yields the more accurate and repeatable results. Calibration of mixed isomer (or similar) standards may utilise summed peak areas, summed peak heights, or measurement of a single component, whichever is the more accurate. If none of these is sufficiently accurate, and particularly if detector response to the components differs on a molar basis, a more satisfactory detection system must be used.
1.8 ANALYTICAL METHODS AND ANALYTICAL PERFORMANCE 1.8.1
Acceptability of analytical methods
A widely accepted criterion for the acceptability of performance of an analytical method is that it should be capable of providing average recovery within the range 70-110%, for all compounds sought by the method and at appropriate concentrations. For problematic analytes, this may represent an unachievable ideal. Where the method does not permit this degree of trueness, the potentially poor accuracy of results must be considered before taking enforcement action. We define recovery as the proportion of analyte remaining at the point of the final determination, following its addition to a test portion of a blank sample immediately prior to extraction. The proportion is usually expressed as a percentage. Average recovery obtained by an analyst provides a measure of the internal bias in results but does not measure that bias against the "true" value. This can only be approached with inter-laboratory studies. Some techniques, such as solid-phase micro-extraction (SPME), certain headspace analyses, or flow-injection analysis (FIA), are incapable of producing a value for recovery, because the determination of "recovery" is the same process as calibration. This does not necessarily mean that recovery is truly 100% but, generally, this does not matter because any difference is automatically compensated for by the calibration process. Similarly, where an internal standard is added at the start of analysis, it is not normally necessary to measure recovery routinely. In this last case, absolute recovery can be 25
A.R.C. Hill, J.R. Startin and R.J. Fussell measured for both the analyte and the internal standard, using external standardisation. Where recovery cannot or is not intended to be determined, the acceptability of the method may be determined on the basis of calibration uncertainty but it is important to recognise that, in addition to precision, accuracy may become an issue at very low concentrations (section 1.7.2). For the determination of fat-soluble pesticides in products where the residues are expressed on a fat basis, the method used to determine the dry weight or fat content must be consistent, otherwise it may contribute significantly to the overall uncertainty of results. 1.8.2 Recovery for determination of acceptability of performance Ideally, recovery of the analytes determined would be measured with each batch of analyses. If this is disproportionately costly, the minimum acceptable frequency of recovery determination may be as given in Table 1.1. In addition, where a residue definition includes several components, of which one can be considered an adequate "marker" of residues of the pesticide, the AQC for screening analysis may be restricted to the marker compound. As an alternative to the above scheme for recovery determination, and especially where samples are analysed primarily to determine whether or not they contain residues at or about some limit (e.g., LCL or MRL), the recovery and calibration can be combined as a qualitative determination. In this case, the recovery is determined routinely by spiking a blank test portion at the level of the appropriate limit and this analysis is also used for calibration purposes. Residues in samples are then scored as being above or below the limit on the basis of the relative responses to the analyte. The percentage recovery is irrelevant, the only essential being that the analyte is measurably detected in the recovery determination. This simple, low-cost, qualitative approach is of particular utility where the majority of samples can be expected to contain no significant residues. The qualitative assessment is effectively "corrected for recovery" but it is difficult to provide sound information on the overall uncertainty of the determinations. This alternative approach can be refined, to make it acceptably quantitative for those pesticides detected in samples, by external calibration of these pesticides in the recovery determination. Depending upon the residue levels found in samples, it might be possible to use a single-point calibration, corresponding to the level of the recovery. If this approach is used routinely, 26
Quality control for pesticide residues analysis the recovery of all pesticides found in samples may be determined retrospectively and thus the uncertainty of results estimated. In cases where truly blank material is not available (e.g., where inorganic bromide is to be determined at low levels) or where the only available blank material contains an interfering compound at an acceptably low level, the spiking level for recovery should be -5 x the level present in the blank material. The analyte (or apparent analyte) concentration in such a blank matrix should be determined from multiple test portions. The concentration should be determined in this way each time a new blank material is to be used. As far as practicable, the recovery of all components defined by the MRL should be determined routinely. Where a residue is determined as a common moiety, routine recovery may be determined by addition of the component that either normally predominates in residues or is likely to provide the lowest recovery. Hitherto, limits have been used to define an acceptable recovery performance, such as "within the range 60-140%" or by the use of control charts and limits of ±2 RSD. Useful though such limits appear to be, the practice has a strong tendency to produce optimistic estimates of the uncertainty of measurement. The reason for this is that, following an unacceptable result and assuming acceptable average values, there is a high probability that if the recovery is repeated once (possibly more times) an acceptable recovery will be achieved and "statistical control" apparently regained. Of course, if the unacceptable recovery is due to equipment failure or other rectified mistake, the determination should be repeated. If not, the population of recovery data is artificially truncated and the analyst is deluded into thinking that the uncertainty of analysis is better than in reality. The analyst should report the recovery data whether they appear to be "good" or "bad". If the uncertainty of recovery indicates that the resultant data are unfit for purpose, a more satisfactory method should be developed or adopted. 1.8.3
Proficiency testing and analysis of reference materials
Determination of average recovery provides a partial indication of bias but it is incomplete and could, in principle, be misleading. In the continuing absence of readily available certified reference materials for most pesticide/product combinations, the laboratory should participate in all available relevant proficiency tests. Although proficiency test data may not represent an ideal way for assessing bias or accuracy, because the basis of the assigned true values may be questionable, they do provide a practical approach.
27
A.R.C. Hill, J.R. Startin and R.J. Fussell Where the result achieved in a test is questionable or unacceptable, the problem(s) should be investigated and, particularly for unacceptable performance, rectified before proceeding with further determinations of the analytes involved. Having said this, it should also be noted that a minority of questionable or unacceptable results might not be due to bias or mistakes, because they might arise as a consequence of statistical chance. The probability of this occurring depends on the uncertainty within the laboratory and this is another reason why control limits on recovery should be avoided. Nevertheless, every effort should be made to identify analytical mistakes before concluding that an adverse result is a consequence of statistical chance, because the probability of this occurring should be low. In-house reference materials may also be analysed regularly to help provide evidence of analytical performance. Where practicable, exchange of such materials between laboratories provides an additional independent check of accuracy. 1.9 1.9.1
CONFIRMATION OF RESULTS Principles
Confirmation of results has two aspects: confirmation of identity and quantity. The former is achieved by producing evidence from various techniques, etc., that supports the identification. The latter is achieved through analysis of additional test portions, to minimise the effects of sub-sampling error. Ad-ditior al confirmation of certain kinds of results would be a waste of time and money, so it is important to define those that are sufficiently important to require confirmation. "Negative" results (i.e., no residue is found or the concentration is below the reporting limit) can be considered confirmed if the recovery and LCL measurement for the batch are acceptable. The two conditions may be met by a single determination (see section 1.8.2) if recovery is at the LCL. In the case of a method that cannot or does not determine recovery, it is sufficient to be able to detect or measure the LCL. In special cases where the accuracy of individual results is unimportant, it is nonetheless important to provide information on the effective uncertainty of results below the LCL. It is impossible to confirm that a sample does not contain a residue but it is sufficient to be able to show that the residue does not exceed the LCL. In the absence of interference, all detection systems used for residues analysis are capable of demonstrating an absence of measurable residues but the criteria 28
Quality control for pesticide residues analysis outlined at the beginning of this paragraph provide the evidence that the results are not false negatives. "Positive" results may require additional confirmation but the requirements should be decided on a case-by-case basis. Generally, the more important the result is, or could be, or the greater the doubt about the result, the greater is the need for confirmation. Results which follow a wellestablished pattern of residues for a pesticide/product combination, or which are clearly of no consequence, may require little or no additional confirmation. Results which exceed an MRL or other action limit (including the detectable presence of a pesticide deemed unacceptable), or which are unusual by virtue of the identity, high quantity or high frequency of the residues found, should be further confirmed. These general rules should not be followed dogmatically-costs and requirements should be balanced-but reported results that are later proven incorrect can have costly consequences. The European Commission has developed a system of "points" for assessment of the extent of confirmation of residues of veterinary medicines in animal products, based on the relative specificity of the mass spectrometric techniques used [18]. This approach is now attracting the interest of pesticide residues analysts, as a means for providing general guidelines for deciding when confirmation is sufficient. However, no such system should be applied dogmatically, as exceptions to the points "rules" will inevitably occur, so assessments must continue to be made critically and not blindly. If the assessment remains doubtful and the result may have important consequences, further confirmation should be sought. 1.9.2
Confirmation by MS
MS, particularly when coupled with GC or LC separation (GC-MS, LC-MS) is the most useful and powerful technique for confirmation of residues. Differences in interface, ion source and analyser design can lead to significant or subtle differences in the relative abundances of ions produced, so reference spectra for the analyte should be generated using the instruments and techniques employed for analysis of the samples. To avoid distortion of ion ratios, the quantity of analyte must not overload the ion source and, depending upon the instrument and data capture system, it may be necessary to avoid generating data from very narrow chromatographic peaks. Reconstructed ion chromatograms (RICs) for diagnostic ions should show peaks of similar retention time, peak shape and response ratio to those obtained from a calibration standard analysed in the same batch. Bearing in mind the constraints outlined in section 1.7.7, ideally, the RIC peak should be 29
A.R.C. Hill, J.R. Startin and R.J. Fussell based on a minimum of seven data points and S/N at the apex should exceed 3:1. Where RICs of ions unrelated to the analyte show peaks of similar retention time and shape to those in RICs from the analyte, or where RICs of unrelated ions are not available (e.g., with selected ion monitoring, SIM), additional confirmation may be required. Where an RIC shows evidence of significant chromatographic interference, it must not be relied upon to quantify or identify residues. For data acquired from scanning, careful subtraction of background spectra is required to ensure that the resultant spectrum of the chromatographic peak is representative. Where ions unrelated to the analyte in a peakaveraged "full-scan" spectrum (i.e., from m/z 50 to 50 mass units greater than the "molecular ion") do not exceed a quarter of base peak intensity in EI spectra, or one-tenth for all other ionisation methods, the spectrum may be accepted as sufficient evidence of identity. Where unrelated ions exceed these limits, and they derive from chromatographically overlapping species, additional evidence should be sought. With EI, the absence of unrelated ions can be used to support identification if the analyte spectrum is very simple. Intensity ratios for principal ions should be within 70-130% of those obtained from the standard. Where an ion-chromatogram shows significant chromatographic interference, it should not be used to determine an intensity ratio. The most abundant ion that shows no evidence of chromatographic interference, and the best signal-to-noise ratio, should normally be used for quantification. EI, performed with acquisition of spectra, or tandem MS (MS/MS) may provide sufficient evidence of identity and quantity in many cases. Singlestage mass spectra produced by other processes (e.g., CI, API) can be too simple for confirmation of identity and further supporting evidence may be required. If the isotope ratio of the ion(s), or the chromatographic profile of isomers of the analyte, is highly characteristic it may provide sufficient evidence. Otherwise, the evidence may be sought using: (i) a different chromatographic separation system; (ii) a different ionisation technique; (iii) MS/MS; (iv) medium/high resolution MS; or (v) altering fragmentation by changing the "cone voltage" in LC-MS. The ions selected for medium/high resolution MS or MS/MS should be characteristic of the analyte, not common to many organic compounds. Where the increased sensitivity obtained by scanning a limited mass range or by SIM is essential, the minimum requirement is for data from two ions of m/z > 200; or three ions of m/z > 100. Intensity ratios obtained from the more characteristic isotopic ions may be of particular 30
Quality control for pesticide residues analysis utility. Additional supporting evidence should be provided where these requirements cannot be met or where doubt remains. Figure 1.4 shows an example of a supposed detection of dieldrin in salmon at 0.02 mg/kg on a fat basis, derived from a single quadrupole instrument operated in EI and SIM mode. Dieldrin produces a wealth of ions, all of low abundance in EI, and even the most abundant ions provided poor S/N in this case, in which the MS is capable only of unit mass resolution. Confirmation using either negative ion chemical ionisation (NICI) or EI with magnetic sector MS at high resolution provided much clearer evidence of both identity and quantity. 1.9.3
Confirmation by an independent laboratory
Where practicable, confirmation of results in an independent laboratory provides strong supporting evidence of quantity. If different determination techniques are used, the evidence will also support identification. 1.10 REPORTING OF RESULTS 1.10.1
Expression of results
Results should normally be expressed as defined by the MRL, with the concentration in mg/kg. Residues below the LCL should be reported as ;P
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European Union legislation on pesticide residues 2.4
SETTING OF EU MRLs
The goal is to have as many MRLs harmonised as possible, at the community level, in the shortest period of time. Harmonised means that the same grade of protection exists among the Member States to avoid intra-community trade problems. This task is difficult to achieve, because there are many possible pesticide/commodities combinations, with a current list of about 180 crops and up to 1000 pesticides in or out of use: then, up to 180,000 MRLs are possible for raw commodities (including animal feed), not to mention all possible MRLs in processed food. Also, first the substance has to have been evaluated under CD 91/414, and consequently to be in annex I to that Directive. The pace of evaluation is not as fast as was first thought when CD 91/414 came into force. At the current speed of evaluation, a decision on the inclusion in annex I of the last substance could be in 2008. The European Commission through Comitology (the way in which the Commission takes decisions in some fields with the vote of the Member States) reached a provisional figure (4 years from the time of first setting the MRL in a specific use) for each commodity/substance combination with which the Member States are pleased. The European Commission and all Member States have to respect the harmonised MRLs although there are always possibilities to change that provisional MRL-if, e.g., a new GAP is required. In the event of non-harmonised MRLs, it is up to the Member States to set them at the national level. This represents a source of trade conflict. To prevent this situation, the conciliation procedure (CD 97/41/EEC) should be invoked. Within a short period of time the exporter and the importer Member States have to exchange information on their MRLs (GAPs, intake assessment, respectively), and agree on an MRL to solve the problem. Another point of difficulty arises when under the World Trade Organisation (WTO) rules, the EU has to respect Codex MRLs; so, at the time of setting MRLs, Codex MRLs have to be taken into account. This means that if the Community does not agree with the Codex MRL, it can set a different one at EU level, and must provide the reasons for not approving it, and notify its partners in the WTO. Hence, it is strictly necessary to follow a program of work for setting and gradually harmonising all the above MRLs. The mechanisms and methods used to fix MRLs are fairly well standardised at the community and global levels, and well-developed data requirements exist at both levels. Member States can authorise the use
47
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L.M. Plaza examined every time an MRL is set for a substance on a crop. Acceptable methodologies are not yet available for systematically looking at aggregate exposure (from other sources, such as the home and workplace) or cumulative exposure (intake from all dietary sources of similarly active substances).
2.5
IMPORT TOLERANCES, EXTRAPOLATION AND LEVEL OF DETERMINATION
The three concepts discussed above are also involved in the process of setting MRLs. In many cases there are no enough data to allow an MRL to be set. This could be when: (i) the crop is not harvested in Europe but it is treated with an active substance used in the EU (usually this is the case for tropical fruit, such as mango or coconuts); (ii) the crop is treated outside Europe with an active substance which is not used yet (e.g., trifloxystrobin on citrus) or is no longer used; is unauthorised because of lack of data (e.g., parathion-methyl); for environmental reasons (e.g., aldicarb) or for applicator-exposure reasons (e.g., lindane); or (iii) because the crop has a critical GAP which is higher outside the EU than in the EU. In the event of one of the three latter situations, an import tolerance can be asked to be set by the Community. The GAP and the tox data-packet should be provided. An import tolerance cannot be granted for banned substances (Dir 79/117/CEE) or substances that have been evaluated and withdrawn because of consumer concern. When there are crops that are similar, such as yams and potatoes, or peaches and nectarines, and the GAPs are comparable-all of them pre- or post-harvest-then, just with a few residue trials and using the data of the similar crop, the MRLs can be set. This is especially interesting for developing countries as they may save resources to achieve the same end. The level of determination (LOD) is the lower level of analytical determination. The analytical determination must be defined (as it depends on the matrix, the substance and the method and equipment) and agreed for all the parties involved, legislators, laboratories, and enforcement and monitoring authorities. The EU approach is to set MRLs at the LOD for non-authorised uses. In all those cases where the complete dossier for evaluating an active substance under Directive 91/414 is not available for the EC, the MRLs for those substances that will be withdrawn from the market in July 2003 will be fixed at the LOD. Fixing the MRL at the LOD 62
European Union legislation on pesticide residues does not mean that the substance will be banned and, on the contrary, not all the banned substances have an MRL set at the LOD.
2.6
MONITORING, REPORTING AND CONTROL
Since 1996, the Commission has made annual recommendations concerning Co-ordinated Community Monitoring Programs for pesticide residues in food. These annual Community Programs complement the national monitoring programs of the Member States. The report of the results of the 1996 program was published late in 1998 and the report for 2001 was posted on the Sanco Internet site in April 2003. The objectives of the programs are to: (i) better estimate the actual exposure of consumers to pesticide residues in food, and (ii) ensure compliance with residues legislation. To fulfil the first objective, the Commission has recently made a call for tender for studying the situation over the first 5 years. The second objective is implicitly to guard against illegal use of pesticides. Trying to cover the biggest number of pesticides and crop combinations, and taking into account the fact that the resources have to be maximised, the system is based on a 3-year rolling program in which for each year a list of pesticides chosen by certain criteria is monitored in a certain number of different commodities. Three of the MRL directives oblige Member States to monitor and report the results of the monitoring. The two relating to cereals and products of plant origin also require the Commission to compile and report on the results. The directive on animal-origin MRLs is weak in this respect, and most Member States report that such monitoring is done in the context of Directive 96/23/EC on "measures to monitor certain substances and residues thereof in live animals and animal products". Besides coordinated Community monitoring program, each Member State develops its own national monitoring program. Following the new sampling Directive 2002/63 (which repealed Directive 79/700/EEC), samples for the national and the EU coordinated programs were taken at different points such as retailers, wholesalers, markets, points of entry, and processing industries. National sampling plans exist in most countries, taking into consideration, e.g., consumption data, production figures, import/export relationships, and risks. For the coordinated program, samples are based on the number of inhabitants.
63
L.M. Plaza In the Community monitoring programs, more than 40,000 samples are analysed annually by the Member States. In the 2001 report, up to 60% of samples contain no residues and MRLs are exceeded in 3-4% of cases. The levels found to date do not present a health risk to consumers. There is a bad public perception of exceedences of MRLs. One easy solution to that problem could be to set higher levels and have fewer exceedences. This solution, of course, is irresponsible. So it is worth having a certain level of MRL violations in the results, owing to tightness in the GAPs, and moving to more target samples rather than random samples, than having a system with not many exceedences but which is less reliable. The top 10 list of pesticides usually found during recent years in the national monitoring plans are: the Maneb group, Chlormequat, Imazalil, Thiabendazole, Iprodione; the Benomyl group, Chlorpyriphos, Procymidone, bromide and ortho-phenylphenol. Extracted from the Explanatory Summary of 2001 monitoring report http://europa.eu.int/comm/food/fs/inspections/fnaoi/reports/annualeu/ indexen.html: "Overall, some 46,000 samples were analysed for, on average, 145 different pesticides. About 93% of the samples analysed were fresh (including frozen) fruit, vegetables and cereals, about 7% were processed products." "In 37% of the fruit, vegetable and cereal samples and processed products, residues of pesticides at or below the MRL (national or EC-MRL) were detected. In 3.6% of all samples, residues above the MRL (national or ECMRL) were found. 60% of the samples contained no pesticide residues. When only fresh products are considered the percentage of MRL exceedences increases to 3.9% instead of 3.6% and the percentage of samples without residues is 59%." "In 2001, the percentage of samples containing multiple residues has significantly increased compared to the 4 previous years. Only the 1996 data showed higher levels, but the 1996 data should be treated with caution, since only 11 countries delivered data." "Like in previous years, mainly fungicides were found on fruit and vegetables whereas, on cereals, the pesticides found were mainly insecticides. The 10 most frequently found pesticides found in 2001 were almost identical with those found in 2000 and the majority corresponded also to those found during 1996-1999." "It appears from the results that the commodities analysed in 2001 were all commodities on which plant protection products are frequently applied, which is in line with the findings of the year 1996 on the same commodities. In 47% of 64
European Union legislation on pesticide residues
the samples, residues of one of the 35 pesticides were found below or at the MRL (national or EC-MRL) and in 2.2% of the samples MRLs (national or EC-MRLs) were exceeded. Only 51% of the samples contained no detectable residues." "The most important pesticide-commodity combinations where detectable residues have been found at or below the MRL and above the MRL were maneb group/lettuce, maneb group/table grapes, iprodione/lettuce and benomyl group/strawberries. With regard to MRL exceedences, the most important pesticide-commodity combinations were maneb group/lettuce and benomyl group/strawberries."
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Samples with residues below or at MRL (national or EC-MRL)
Samples with residues above MRL (national or EC-MRL)
RAPID ALERT SYSTEM IN FOOD AND FEED
The RASFF is based on a network involving Member States (in this case, Member States means all states that belong to the European Union and also those states that fall in the scope of the EEA Agreement, which at the moment are Norway, Liechtenstein and Iceland), the Commission and the European Food Safety Authority (EFSA). The idea is to have a rapid way of transmitting information and action to be taken among the members of
65
L.M. Plaza the system, on direct or indirect risk to human health from food or feed. Its principal objective is to prevent the placement on, or the recall from, the community market of foodstuffs that pose a serious risk to the health of the consumer. The legal basis of RASFF dates from 1984, Council Decision 84/133/EEC, as a general short-term surveillance and alarm system, but after a certain number of amendments and CD 92/59/EEC "on general product safety", where the scope was limited to food and industrial products but not feed, the current legal base was established: Regulation (EC) No. 178/2002 of 28 January 2002 "laying down the general principles and requirements of food law, establishing the European Food Safety Authority and laying down procedures in matters of food safety", chapter IV. The Regulation introduces, or refines, among other things in relation with the RASFF: new procedures, implementing measures, the feed sector and food imports from outside EU and the role of EFSA. There are two levels of information in the RASFF: alert (see Table 2.9) and information. Alert notification must fulfil the following conditions: (i) food on the market, (ii) more than one Member State involved, (iii) immediate action is required. Information notification: (i) immediate action not required, (ii) provide useful information. So, depending on the risk assessment and on the state of the food/feed (on the market, at a EU border post, or already consumed), the Member States trigger one of the two kinds of notification. The RASFF team in SANCO receives it and evaluates it and communicates the result of the assessment and the measures already taken by the Member States (withdraw or recall the product from the market or stop the consignment at the border). To assess the risk, it has to take into account the fact that risk is a function of the hazard (toxicity) and exposure. The ADI and/or ARfD express the toxicity. In the exposure, some factors such as the highest portion consumed or the variability factor (see Tables 2.10 and 2.11) in having residues in the composite sample, etc., must also be taken into account. So, in many cases, MRLs' violations from food that is a very minor part in the diet (tea, spices, some herbs, etc.) are not triggering any alert; in others, when the substance is very toxic, just a small amount could represent a big risk for the consumer. Focusing on pesticides alerts, where MRLs are exceeded it is up to the Member States to withdraw the product from the market or take other measures, based on their own risk assessment. They should notify the results immediately to the Commission that will make the risk management and transmit the outcome of the evaluation (alert, information, or even no notification) using the Rapid Alert System.
66
European Union legislation on pesticide residues TABLE 2.9 Example of an Alert communication: RAPID ALERT SYSTEM FOR FOODSTUFFS SYSTEME D'ALERTE RAPIDE DENREES ALIMENTAIRES SCHNELLWARNSYSTEM FUR LEBENSMITTEL DIRECTIVE 92/59/EEC-DIRECTIVE 92/59/CEERICHTLINIE 92/59/EWG NOTIFICATION GENERAL INFORMATION-INFORMATIONS GENERALESALLGEMEINE INFORMATIONEN: 01: NOTIFYING COUNTRY: PAYS DE NOTIFICATION: XXXXXXXXX MELDENDES LAND: 02: DATE OF NOTIFICATION: DATE DE NOTIFICATION: 8-03-2003 TAG DER MELDUNG: PRODUCT-PRODUIT-PRODUKT: 03: CATEGORY OF PRODUCTS: CATtGORIE DE PRODUITS: PRODUKTKATEGORIE: 04*: PRODUCT NAME/TRADE NAME: NOM DE PRODUIT/DENOMINATION COMMERCIALE: PRODUKTBEZEICHNUNG/ (VERKEHRBEZEICHNUNG): 05a*: IDENTIFICATION OF THE LOT: IDENTIFICATION DU LOT: LOSKENNZEICHNUNG: 05b: PUBLIC HEALTH CERTIFICATE: CERTIFICAT DE SALUBRITE: GENUSSTAUGLICHKEITSBESCHEINIGUNG:
Fruit and vegetables
Grapes
continued
67
L.M. Plaza 06*:
07*:
MINIMUM DURABILITY DATE OR BEST BEFORE DATE: LA DATE DE DURABILITI MINIMALE OU LA DATE LIMITE DE CONSOMMATION: MINDESTHALTBARKEITSDATUM ODER VERBRAUCHSDATUM: DESCRIPTION OF THE PRODUCT: DESCRIPTION DU PRODUIT: PRODUKTBESCHREIBUNG:
ORIGIN-ORIGINE-HERKUNFT: 08*: NAME OF THE MANUFACTURER: NOM DU FABRICANT: NAME DES HERSTELLERS/ ABPACKERS: 09*: VETERINARY APPROVAL NUMBER: NUMERO D'AGREMENT VtTERINAIRE: VETERINARKONTROLLNUMMER: 10: PERSON TO CONTACT: PERSONNE A CONTACTER: ANSPRECHPARTNER BEIM HERSTELLER: 11*: COMPLETE ADDRESS: ADDRESSE COMPLETE: VOLLSTANDIGE ANSCHRIFT: 12*: COUNTRY OF ORIGIN: PAYS D'ORIGINE: HERKUNFTSLAND: 13*: IMPORTER OR RETAILER: IMPORTATEUR OU DISTRIBUTEUR: IMPORTEUR ODER HANDLER: 14a*: DISTRIBUTION TO MEMBER STATES: DISTRIBUTION DANS LES ETATS MEMBRES:
White seedless grapes
xxxxXXXXX xxxx
xxxxxx
XXXXXxxx
continued
68
European Union legislation on pesticide residues
14b:
VERTEILUNG IN DEN MITGLIEDSTAATEN: EXPORTED TO THIRD COUNTRIES: EXPORTATION AUX PAYS TIERS: AUSFUHR ZU DRITTLANDERN:
DANGER-DANGER-GEFAHR: 15': NATURE OF DANGER: NATURE DU DANGER: ART DER GEFAHRDUNG: 16a*: RESULTS OF THE TESTS: RESULTATS DES ANALYSES: ERGEBNISSE DER UNTERSUCHUNGEN: 16b*: SAMPLING DATE: DATE DE L'ECHANTILLONNAGE: DATUM DER STICHPROBEN ENTNAHME: 16c*: PLACE OF THE TESTS: PLACE DES ANALYSES: ORT DER UNTERSUCHUNGEN: 17*: METHODS OF ANALYSIS USED: MITHODE D'ANALYSE UTILISEE: UNTERSUCHUNGSMETHODE: 18*: PERSONS AFFECTED: VICTIMES: BETROFFENE PERSONEN/ GESCHADIGTE: 19: TYPE OF THE ILLNESS: TYPE DE MALADIE: ART DER ERKRANKUNG:
Methomyl > NESTI
Methomyl 0.42 mg/kg 8-5-200x
xxxxxxx
GC-MS
MEASURES ADOPTED-MESURES PRISES-MABNAHMEN: 20*: VOLUNTARY MEASURES: MESURES VOLONTAIRES: FREIWILLIGE MAJ3NAHMEN DES INVERKEHRBRINGERS: 21*: COMPULSORY MEASURES: MESURES IMPOSEES: continued 69
L.M. Plaza
22*:
23:
24:
25:
AMTLICHE MABNAHMEN: JUSTIFICATION: JUSTIFICATION: BEGRUNDUNG/RECHTSGRUNDLAGE:
Methomyl: EU/MRL 0.05 for table grapes
SCOPE: NATIONAL OR REGIONAL PORTEE: GELTUNGSBEREICH: DATE OF ENTRY INTO FORCE: DATE D'ENTREE EN VIGUEUR: DATUM DES INKRAFTTRETENS: DURATION: DUREE: GELTUNGSDAUER:
OTHER INFORMATION-AUTRES INFORMATIONS-SONSTIGE INFORMATIONEN: 26*: MINISTRY: Health MINISTERE: ZUSTANDIGES MINISTERIUM: 27*: PERSON TO CONTACT: xxxxxxx PERSONNE A CONTACTER: ANSPRECHPARTNER: 28: OTHER INFORMATION: AUTRES INFORMATIONS: SONSTIGE INFORMATIONEN: 29*: CONFIDENTIAL: CONFIDENTIELLES: VERTRAULICH: 30*: IF YES, WHY: SI OUI, POURQUOI: WENN JA, BEGRiNDUNG: In this case, using the values from WHO and JMPR of the unit weight for table grapes of 0.5 kg and large portion of 0.485 kg, variability factor of 5, and the value of the ARfD of 0.02 mg/kg bw in a worst case scenario
70
European Union legislation on pesticide residues of a child of 15 kg, the outcome (according to the formulae from the WHO) from the Commission was that methomyl exceeded the ARfD by 381%; so it was an alert. TABLE 2.10 DEFAULT VARIABILITY FACTORS IF NO VARIABILITY FACTOR IS AVAILABLE FROM TRIALS DATA (SOURCE: JMPR; PSD) Commodity Variability Commodity Variability Commodity Variability factor factor factor Citrus fruit Grapefruit Lemon Mandarins and other soft citrus Oranges Limesa
7 7 7
7 7
Pome fruit Apple Pear
7 7
Quince
7
Stone fruit Apricot Peach Plum
7 7 7
Nectarine
7
Berries Table grape (bunches)
5
Guava Kiwi fruit Pawpaw/ papaya Pineapplea
Root and tuber vegetables Beetroot Carrot Celeriaca Jerusalem artichoke Potato Parsnip Swedea Sweet potato Turnipa Yama
7 7 7 7
Cucurbits Cucumber Courgette/ zucchini Melonsa
7 7 5
Watermelon Marrow
5 5
7 7 7 7
Pumpkina
5
Brassica Broccoli
7
7 7 7
Cauliflower Cabbage Chinese cabbage Kohlrabi
7 7 7
Bulb and stem vegetables Onions
7
Fennel bulb
7
Lettuce and leaf vegetables Lettucea Spinach
Chicory/ witloof
5 5 7 7
5 1
7
continued
71
L.M. Plaza TABLE 2.10 (Continuation) DEFAULT VARIABILITY FACTORS IF NO VARIABILITY FACTOR IS AVAILABLE FROM TRIALS DATA (SOURCE: JMPR; PSD) Commodity Variability Commodity Variability Commodity Variability factor factor factor
Miscellaneous fruit Avocado Banana Fig Mango
7
7 7
Fruiting vegetables Tomato Pepper, sweet
7 7
Pepper, chilli Auberginea
7 7
7 7
Stem vegetables Asparagus Celery Globe artichoke Leek Rhubarb
1 7 7 7 7
aA single portion of these commodities usually consists of less than one unit. TABLE 2.11 Pesticides for which no ARfD is necessary according to JMPR evaluations: Acibenzolar-S-methyl Amitrole (aminotriazole) Azimsulfuron Azoxystrobin Bitertanol Chlorpyrifos-methyl Cinidon ethyl
Clethodim Cyhalofop-butyl 2,4-D DDT Diflubenzuron Diphenylamine Diquat (dibromide) Ethofumesate
72
Ethoxyquin Fenhexamid Ferric phosphate Florasulam Flupyrsulfuron methyl Fluroxypyr Glyphosate (including trimesium, also known as sulfosate) Imazalil (also known as enilconazole) Iprovalicarb Isoproturon Kresoxim-methyl Metalaxyl-M Methoprene Metsulfuron 2-Phenylphenol (including sodium salt; also known as sodium 2-phenylphenate)
Piperonyl butoxide Prohexadione calcium Propargite Propyzamide Prosulfuron Pyridate Pyriproxyfen
Quintozene Spinosad Spiroxamine Sulfosulfuron Thiabendazole Thifensulfuron (also known as thiameturon) Thiophanate-methyl Triasulfuron
European Union legislation on pesticide residues 2.8
ACTIVITIES IN INTERNATIONAL FORA
There are some other organisations dealing with pesticide residues such as: the OECD, the World Trade Organisation, the Codex Alimentarius, the ACPLom6 countries. 2.8.1
The OECD
The "Pesticides Working Group" provides for the exchange of views and information on pesticides: some of the issues covered here are: work-sharing, to prevent duplicating work at the OECD level and having the same level of protection; the importance of zoning, etc. 2.8.2
The World Trade Organisation
Under the agreement on Sanitary and PhytoSanitary (SPS agreement) the EU has the obligation to notify in advance all decisions taken about MRLs; then 60 days are allowed from the date of the notification for comments from the other partners at the WTO level. At the same time, the EU may have comments on other legislation from other countries in the WTO. In the event that any comments arrive, the Community has the obligation to take them into account at the time of approving the legislation concerned. 2.8.3
The Codex Alimentarius commission
The work of the Codex Alimentarius Commission, and more particularly of the Codex Committee on Pesticide Residues (CCPR), deals with consumer safety. The CCPR base their decisions on the WHO-FAO Joint Meeting on Pesticides Residues (JMPR). The CCPR has the role of risk manager and the JMPR of risk assessor. The JMPR sets ADIs and fixes ARfDs for active substances, and the CCPR sets the Codex MRLs. Sometimes their values differ from the values obtained at EU level. When this happens, a trade problem may arise at the international level; then the EU may be taken to a trade court at the WTO level to defend its position with a scientific basis. 2.8.4
The ACP-EC Partnership Agreement
The ACP-EC Partnership Agreement signed in Cotonou on 23 June 2000 states that the Community notifies ACP countries of technical measures taken in the area of pesticides when they are likely to affect the interests of one or more ACP States. 73
L.M. Plaza Many decisions of exclusion from the annex I listing have had some negative impacts (MRLs at LOD) in developing countries where the use of generic substances is a common practice, as they are cheaper than substances under patent. There is also a negative impact at EU level, where there may be problems of importing to the Community some tropical fruit and vegetables. In anticipation of these impacts, the Commission has established two development programs. The first of these is aimed at promoting Integrated Crop Management in these countries, lessening their dependence on pesticides use, and reducing where possible the residue levels found in their commodities. The second, the "Pesticides Initiative", is aimed at promoting better coordination and information gathering in the ACP area with a view to providing, in good time, the data necessary for the Commission to set MRLs for tropical fruit and vegetables. 2.9
FUTURE TRENDS
Globalisation is making the world smaller. The main countries (and the international organizations as Codex and the OECD/OCDE) are much closer than before in evaluating and setting pesticide MRLs. The aim is to smooth the rules among them and avoid trade problems by trying to achieve the same standards, or as many equivalents as possible. The following solutions are in progress: ·
·
The sharing of information among administrations is growing, as in the OECD/OCDE. Why should one waste resources in evaluating substances if another organisation or country has already evaluated them? Data protection and patents seem to be problems, as it is very expensive to generate the different dossiers for the same substance. Increasing the resources of the JMPR could also improve the situation, as the evaluation of the Codex is very slow.
At the EU level, the Commission proposal on pesticide legislation is under current discussion at the European Parliament and Council. The result of this discussion at this stage is difficult to foresee. Many details need to be reflected on, such as the default value of 0.01 mg/kg as the level of determination; the role of the EFSA, the inclusion of cumulative and aggregate pesticides in the setting of MRLs, the use of monitoring data in certain cases instead of GAPs, the choice of which commodities should be in the list, etc. Whatever the state of this Regulation proposal at the end of the Council and Parliamentary discussion, it is clear that it reflects a public wish for quick harmonisation and simplification of the current situation.
74
Chapter3
Sample handling and clean-up procedures I Stewart L. Reynolds
3.1
INTRODUCTION AND SCOPE
This chapter does not include sampling techniques, which are described by Codex [1] and have been adopted by the European Commission [2], but begins at the point when the sample is received at the laboratory-with "the laboratory sample". The following text focuses predominantly on conventional solvent extraction techniques used in multi-residue methods (MRMs) for the extraction of pesticides, from "non-fatty" foods such as fresh fruits, vegetables and grains. Accelerated solvent extraction (ASE), microwave extraction, supercritical fluid extraction (SFE) and solid-phase extraction (SPE) techniques are covered in chapter 4. Similarly, gel permeation chromatography (GPC) is the only clean-up technique discussed in this chapter, and other clean-up techniques, such as adsorption and immuno-affinity, are described in more detail in chapter 4. 3.2
3.2.1
LABORATORY SAMPLE PREPARATION
Portion of the laboratory sample to be analysed
Before any pesticide residue analysis is undertaken by a laboratory, it is important to know for what purpose the resultant data will be used. In general, screening for pesticide residues in food is requested for two main reasons: 1. To monitor good agricultural practice (GAP), by checking for compliance with international (Codex) standards accepted by the World Trade Organisation (WTO), or national legislation, i.e., ensuring that maximum residue limits (MRLs) are not exceeded, and/or that non-approved pesticides have not been used. Comprehensive Analytical Chemistry XLIII Fernindez-Alba (Ed.) (C 2005 Elsevier B.V. All rights reserved
75
S.L. Reynolds 2. To provide residue data which can be used to estimate consumer dietary intakes and to subsequently perform risk assessments. The portions of the commodities to which the MRLs apply are clearly stipulated by Codex and have been adopted into many countries' national legislation. Food commodities are classified into groups, e.g., root and tuber vegetables (carrots, potatoes, radishes, etc.) or stone fruits (apricots, cherries, peaches, etc.). Codex also provides information on how to prepare the laboratory sample for analysis (i.e., to prepare the analytical sample) once it has arrived at the laboratory, e.g., by removal of soil, decomposed leaves, stalks, stems or stones. If residue analysis is to be undertaken for dietary intake purposes then the portion of the commodity that is to form the analytical sample might be quite different from that required for MRL compliance purposes. A typical example is banana. Bananas are classified by Codex as "assorted fruits with inedible peel". For MRL compliance purposes, only the crowns and stalks that have usually already been removed from bananas prepared for retail sale would be removed before analysis. However, if consumer exposure is to be assessed, then the bananas would be peeled and the skins discarded, to reflect normal consumer practice. Alternatively, the bananas could be processed and analysed as a whole (including the skins, but not the crown and stalks), and if available, an appropriate "processing factor" could subsequently be applied to the residue data so generated. In addition to home processing, e.g., washing, peeling, cooking, etc., many raw agricultural commodities are subjected to commercial food manufacturing processing before consumption. The estimation of consumer exposure, and hence consumer risk, requires information on residue levels in edible portions of raw agricultural materials and processed (home and/or commercial) commodities. FAO [3] states that the processing factor should be explicitly defined in terms of residue levels, as follows: Processing factor = the residue level (mg/kg) in the processed product/the residue level (mg/kg) in the raw agricultural commodity. The following processing methods have been identified as being widely used by industry and/or consumers: * drying (e.g., dates, figs, grapes) · canning (e.g., fruits, vegetables) · juicing (e.g., citrus fruits, tomatoes) * milling (e.g., wheat grain into flour and bran) * baking of bread · brewing (e.g., hops), wine production (e.g., grapes) 76
Sample handling and clean-up procedures I · · ·
oil extraction and refining (e.g., olives, rapeseed) refining (e.g., sugar beet) cooking, including boiling (e.g., potatoes, rice, vegetables), frying (e.g., potatoes, meat) and microwave cooking
Studies undertaken to produce processing factors must mirror home processing and/or commercial processes as closely as possible. These processing factors can then be applied to the result obtained from analysis of the raw commodity. 3.3 3.3.1
LABORATORY SAMPLE PROCESSING Homogeneity
The analytical sample is likely to consist of a number of individual units and could weigh more than 2 kg. As the whole of the analytical sample will not be analysed, it is important to homogenise the individual units so that representative sub-samples (test portions) may be withdrawn. Sub-sampling error due to heterogeneity of residue distribution in the analytical sample can contribute greatly to the uncertainty surrounding the subsequent residue data that are generated from test portions. Such errors will be increased as the size of the test portion taken is reduced. As most modern methods tend to utilise relatively small test portions (2-10 g) in order to save time, materials and money, the preparation of essentially homogeneous analytical samples is paramount. A recent study undertaken by Young et al. [4] involved the comminution of apples, cabbage and green beans containing field-incurred residues of p,p'-methoxychlor. A 40 qt vertical cutter mixer (as stipulated in the US FDA Pesticide Analytical Manual [51) was used to comminute large samples comprised of many individual fruits or vegetables. Test portions of 100, 50 and 25 g taken from the resultant homogenates of all three crops produced equivalent results. However, statistically significant differences were obtained for green beans with test portions of 2 g and cabbages with test portions of 10 g. It should be noted that Young et al. [4] used a lengthy comminution time (5 min) and that they chose to use a particularly stable pesticide, p,p'-methoxychlor. Comminution may be achieved by using an appropriate cutting/grinding device, and there are many suitable bowl choppers, mills and food processors available. Most are electrically powered but some may require manual intervention to ensure good mixing of the comminuted material. The degree of homogeneity obtained will not only be dependent on the type of equipment
77
S.L. Reynolds used, but also on a number of other key factors. For example, if a bowl chopper is used: 1. Length of comminution. In general, the longer the equipment is running the greater the disintegration of the sample, although after a certain time hardly any further disintegration will occur. It is important to consider analyte stability (see section 3.3.2). As the chopping/cutting process continues, more heat is generated within the sample. Some cutting devices are fitted with cooling jackets that can be used to prevent undue heating of the sample during comminution. 2. Design of the cutting device. This is particularly important and there are a number of design features that are necessary for rapid comminution. The motor must have the necessary power to match the capacity of the bowl. The blades should be broad and inclined and arranged at different levels. A mixing baffle will ensure a more thorough intermixing of the sample. 3. Sharpness of the cutting blades. With any cutting/chopping device, after much use the blades will become blunted and less effective. 4. Nature of the sample. Some materials are relatively fragile and disintegrate easily and rapidly to a small particle size, whilst others are much harder, fibrous or have tough skins, and will take much longer to achieve the same particle size. Materials that combine both soft and fibrous/tough/hard components are usually the most difficult to homogenise. 5. Correct amount of sample. When using any cutting/chopping device it is important not to over- or under-fill the equipment bowl with sample. Too little sample may result in poor comminution, whilst too much sample will not only produce a similar effect, but could also result in spillage from the equipment. 3.3.2
Analyte stability
The potential for loss of certain pesticides during sample processing has been known for many years. Losses of dithiocarbamate fungicide residues during sample processing of fresh plant material was first recognised in 1971 when Howard and Yip [61 demonstrated that significant losses ofmaneb occurred after addition to freshly chopped kale. Hill et al. [7] concurred that this instability problem could be overcome by adopting one of the following strategies: 1. Take the whole laboratory sample and analyse as a single determination without disintegration. However, this is seldom practical as more than a single determination is often required, and large volume glassware and large quantities of reagents would be needed.
78
Sample handling and clean-up procedures I 2. Cut segments (causing the minimum possible disruption to the sample tissue). With this approach the sub-sampling error will be high, and it is prudent to analyse a number of replicate segments, and calculate the mean result. 3. Use cryogenic processing to slow down degradation of the dithiocarbamate residue (see below). Comminution processes are normally performed at room temperatures (20-25°C), but it is important to realise that enzymes and other labile chemicals will be released from the disrupted tissues, which may react with pesticide residues if present in the sample. As simple chemical reaction rates decrease as the temperature decreases, one way of eliminating, or at least reducing, pesticide losses is to freeze the sample prior to processing and then comminute it in the presence of "dry ice" (solid carbon dioxide). Such processing is often referred to as "cryogenic milling" and comminution can take place at more than 40°C below room temperature. Fussell et al. [8] demonstrated that losses of bitertanol (95%), heptenophos (50%), isofenphos (40%), and tolylfluanid (48%), which occurred at room temperature, could be eliminated by using cryogenic milling. Also losses of dichlofluanid (54%) and etridiazole (40%) at room temperature were reduced to 10 and 14%, respectively, at - 20°C. Following cryogenic milling, it is advisable to store the samples in open bags in the freezer for at least 24 h to allow the dry ice to completely evaporate before weighing out test portions for analysis. 3.4
3.4.1
EXTRACTION OF PESTICIDE RESIDUES WITH ORGANIC SOLVENTS Extraction techniques
In most classical methods for the determination of pesticide residues, the pesticides are extracted from samples using a single organic solvent, a mixture of organic solvents, or an aqueous/organic solvent mixture. The choice of extraction equipment may be influenced by the degree of comminution that has taken place during sample processing (see section 3.3). Extremely finely comminuted analytical samples may only need to be shaken/agitated with the extraction solvent using a shaker or vortex mixer to achieve maximum extraction efficiency. If possible, the extraction efficiency should be checked using test samples containing known concentrations of incurred residues. Analytical samples that have received little or no laboratory processing will require further comminution and this can be achieved as part of 79
S.L. Reynolds the extraction procedure. Bottom and top-driven macerators/blenders (e.g., Ultra Turrax or equivalent) and sonicators may be used to comminute the sample and mix it with the extraction solvent simultaneously. Thus the analyte should be in equilibrium with the solvent and any insoluble sample matrix. 3.4.2
Properties of organic solvents
There are a number of solvents and solvent mixtures that can be chosen to extract pesticide residues from foods. Choice, in terms of extraction efficiency, will be largely dependent on the polarity of analytes that are to be targeted. Non-polar pesticides, e.g., the persistent organochlorines, can be readily extracted using non-polar, hydrocarbon solvents, whereas the more polar pesticides, e.g., many of the organophosphorus compounds, will require a low to medium polarity solvent for efficient extraction. The polarity of a solvent is broadly reflected in its dielectric constant, and values for the solvents most commonly used for the extraction of pesticides from food and environmental samples are given in Table 3.1. If sample extracts must be concentrated before clean up or determination, then the boiling point of the solvent is also important, and these values are also presented in Table 3.1. However, it is worth remembering that many food samples, particularly fruits and vegetables, contain a high proportion of
TABLE 3.1 Important physical properties of solvents [9] Solvent
Dielectric constant (20°C)
Acetone Acetonitrile Cyclohexane
20.7a 37.5
Dichloromethane Ethyl acetate Hexane Methanol Pentane Petroleum ether Water
2.0 9.1 6.0a 1.9 32.6a 1.8 78.5 --
"25C.
80
Boiling point (°C)
Vapour pressure (kPa at 25°C)
56 82 81 40
30.8 11.8 13.0 58.2
77 69
12.6 20.2
65 36 30-60
16.9 68.3
100
Sample handling and clean-up procedures I water. If a water-miscible extraction solvent, such as acetone, is used then the resultant sample extract will also contain a high percentage of water that may need to be removed prior to concentration. 3.4.3
Basic safety with solvent usage
The two most important considerations with regard to the use of organic solvents within the laboratory are flammability and toxicity. With the exception of dichloromethane and water, all the solvents listed in Table 3.1 are readily flammable at room temperature. It is therefore essential that adequate ventilation is provided in the extraction areas of laboratories, and that all electrical equipment utilised therein are "spark-proof'. Indeed all extraction and evaporation procedures should be performed in fume cupboards. As well as the potential dangers posed by flammable solvents, worker inhalation exposure must also be considered. Table 3.2 gives the flash points and exposure limits for some of the solvents commonly utilised in the laboratory. 3.4.4
Solvents used as extractants in multi-residue methods
Many MRMs have been developed over the past four decades that allow the simultaneous analysis of a wide range of pesticide residues in a variety of different foods commodities. Without MRMs, residue analysts would be faced with using literally hundreds of specific, single residue methods (SRMs),
TABLE 3.2 Flammability and toxicity data for solvents [10] Solvent
Flash point (°C)
Long-term exposure limit (8-h period) (ppm)
Long-term exposure limit (8-h period) (mg/m3 )
Acetone Acetonitrile Cyclohexane Dichloromethane Ethyl acetate Hexane Methanol Pentane Petroleum ether
- 20 6 - 20 -4 - 22 11 -40 - 22 to - 40
500 40 100 100 200 20 200 -
1210 68 350 350 72 266
81
S.L. Reynolds even though many of them would be very similar, if not the same. However, as it is impossible to create a single set of optimum conditions for extraction and clean up of all possible pesticide/commodity combinations, MRMs must have limitations. With all MRMs, and in particular multi-class MRMs, recoveries approaching 100% for all pesticides from all possible food matrices is unlikely. Numerous different organic solvents, and mixtures of organic solvents, have been used to extract a wide range of pesticides with different physicochemical properties from foods. The use of three solvents (acetone, ethyl acetate (EtAc) and acetonitrile (MeCN)) has predominated in MRMs and all three continue to appear even in the most recent publications. It seems that residue analysts still cannot decide which of these solvents is the most suitable for multi-residue extraction. Acetone, MeCN and EtAc have all been, and still are being, used in hundreds of analytical laboratories around the world to extract both non-polar and polar pesticides from a wide diversity of raw agricultural materials and processed food products. Acetone and MeCN are both fully miscible with water, whereas EtAc exhibits only low miscibility with water. MeCN and acetone extracts from fresh fruits and vegetables will contain water coincidentally extracted from the sample. Schenck and Lehotay [11] noted that it is usually necessary to remove this water before any gas chromatographic determinations can be made, and this can be achieved by partitioning the pesticides from the aqueous/organic extract into a water-immiscible solvent. 3.5
3.5.1
HISTORICAL DEVELOPMENT OF MULTI-RESIDUE METHODS BASED ON THE USE OF ACETONITRILE, ACETONE AND ETHYL ACETATE AS EXTRACTION SOLVENTS Acetonitrile
MeCN has the disadvantage of being both more expensive and more toxic than acetone and EtAc. However, it also has advantages over acetone and EtAc, not least is that, because of its higher polarity, much less lipophilic material, such as oils and chlorophyll and to a lesser extent waxes, are co-extracted with the pesticides. One of the first MRMs to be published was by Mills et al. [12] in 1963. They used MeCN to extract organochlorine pesticides (OCs) from a range of different fruits and vegetables. These relatively non-polar compounds were then partitioned into petroleum ether (PE) after the addition of a large 82
Sample handling and clean-up procedures I volume of water and a small volume of saturated salt (NaCl) solution. The PE solution was then applied to a Florisil column as a clean-up step, prior to determination using a gas chromatograph (GC) fitted with an electroncapture detector. By the late 1960s the widespread use of organophosphorus (OP) insecticides in agriculture meant there was a requirement for a number of these predominantly more polar compounds to be included in MRM analytical suites. The partition using non-polar PE was unsuitable for polar compounds and meant that recoveries of many OPs through this step would be poor. Alternative methods were developed which retained the use of MeCN as the extraction solvent, but involved alternative partitioning solvents and/or cleanup techniques. In 1971, Storherr et al. [13] used the higher polarity dichloromethane (DCM) to replace the non-polar PE and acid-treated charcoal to replace the Florisil. This method was used to determine a wide range of OPs in samples of fruits and vegetables. By the early 1990s MeCN was being used to extract more than 100 target analytes from many different classes of pesticide, e.g., organochlorines, organophosphorus compounds, carbamates, etc. In 1991, Ton Joe and Cusick [14] used MeCN to recover 143 pesticides from 13 different crop samples. They extracted 50 g of chopped sample with 100 ml of MeCN, and added solid NaCl to the filtered extracts to effect a separation into two phases. An aliquot of the upper MeCN phase was dried and concentrated before using splitless injection into a gas chromatograph fitted with a mass spectrometer, without any clean up. In the same year, Lee et al. [15] used the identical MeCN extraction procedure, but added an SPE (C-18) cartridge clean-up step so that the extracts were compatible with selective GC detectors (FPD and ECD) and HPLC. In 1995, Fillion et al. [16] also adopted the same extraction procedure, but used charcoal-Celite to effect a clean up for 199 pesticides with GC-MS and HPLC-fluorescence detection. In 1999, Cook et al. [17] again used the same basic extraction procedure with a variety of SPE clean-up steps to analyse 89 pesticides in a wide range of fruits and vegetables. 3.5.2
Acetone
Acetone is the least toxic, least expensive, and most volatile of the three solvents. In 1971, Becker [18] utilised acetone as a solvent to extract OC and OP pesticides from samples of plant-based materials. However, his method per se is unlikely to be used in laboratories in the 21st century as it involves
83
S.L. Reynolds the use of benzene in the clean-up step. Luke et al. [19], 4 years later, developed an MRM that included not only OCs and OPs, but also various organonitrogen (ON) compounds. Samples of fruits and vegetables (100 g) were extracted with 200 ml of acetone and the extracts then partitioned into a PE/DCM mixed solvent followed by a Florisil clean up similar to that used by Mills et al. [12]. In 1981, Luke et al. [20] improved this procedure by eliminating the Florisil clean-up step and adding petroleum ether following the initial concentration to remove traces of DCM. About the same time, Specht and Tillkes [21] published their MRM for 90 pesticides in samples of both vegetable and animal origins. Like Luke, they also utilised DCM to partition the pesticides from the aqueous acetone extracts, but added a GPC clean-up step. The method was adopted in Germany by the DFG into their Manual of Pesticide Residue Analysis. The status and popularity of this manual amongst residue analysts meant that the Specht and Tillkes DFG method (S-19) became widely used during the 1980s and early 1990s, not only in German laboratories, but also in many other laboratories throughout Europe. By the early 1990s, analysts were coming under increasing pressure to eliminate usage of chlorinated solvents, such as DCM. In 1994, Koinecke et al. [22] investigated the use of several less toxic solvents as possible replacements for DCM. They concluded that cyclohexane, light petroleum (also known as petroleum ether) and tertiary butyl methyl ether all gave acceptable recoveries for a wide range of pesticides, including those of high water solubility, by partitioning from acetone extracts of plant materials. A year later, Specht et al. [23] published a paper that updated the DFG method S-19 by replacing the DCM with EtAc/cyclohexane (1:1) in the liquid-liquid partition. This publication also simplified the S-19 method by combining the acetone extraction step with the liquid-liquid partition step. An added bonus was that EtAc/cyclohexane was used as the GPC elution solvent, so no solvent exchange was required for the sample extracts prior to clean up. In more recent years, SPE has been used by Casanova [24] and Nordmeyer and Their [25] to replace the DCM partition from aqueous/acetone extracts. Because the word "extraction" appears in SPE, it is easy to assume that this is simply an alternative to solvent extraction, whereas in most methods SPE acts as a clean up, not an initial extraction, step. Adou et al. [26] used acetone in combination with other solvents to apply a newer technology, pressurised liquid extraction (PLE), also known commercially as ASE, to automate the extraction procedure and reduce analysts' exposure to solvents. SPE and PLE are covered in detail in the following chapter of this book.
84
Sample handling and clean-up procedures I 3.5.3
Ethyl Acetate
Whilst MeCN and acetone are water miscible, EtAc exhibits only very low water miscibility. The main advantage of EtAc is that the small amounts of water present in sample extracts can be easily removed by the addition of anhydrous salts, intended for removing water, without the need to perform any additional liquid-liquid partitioning. In comparison with the other two solvents EtAc is less polar, and with oily samples, such as avocados and animal products, more non-polar lipophilic materials may be present in the extracts. One of the first MRMs to be based on an EtAc extraction was published by Watts et al. [27] in 1969. They obtained good recoveries of 60 OPs from apple, carrot and kale crops extracted with EtAc. The extracts were cleaned-up on a charcoal column and the pesticides determined using GC-NPD. For the next decade there appeared to be a paucity of published methods that employed EtAc, and it was not until the late 1980s that EtAc gained in popularity as the primary extraction solvent. Roos et al. [28] used EtAc as an extractant for OC and OP residues from a wide range of foods, including fruits and vegetables. They used a GPC column to clean up the sample extracts and reported recoveries of OCs from cereal grains when using EtAc that were virtually the same as those obtained using acetone. In 1994, Ferndndez-Alba et al. [29] used EtAc to extract residues of OCs and pyrethroids from fruits and vegetables. They used silica gel cartridges to effect clean up of the extracts and employed GC-ECD and GC-MS to determine the pesticides. In the same year, Holstege et al. [30] used EtAc modified with 5% ethanol (EtOH) to extract OCs, OPs and carbamates from a range of both plant and animal-based commodities. They reported that the EtOH was required to produce quantitative recoveries of the most polar OPs (acephate, methamidophos and monocrotophos) from water, without affecting the recoveries of the most non-polar OP pesticide, chlorpyrifos. In 1999, Obana et al. [31] also used EtAc to extract pesticides, of mixed classes, from fruits and vegetables. They used a high-speed homogeniser to comminute the samples thoroughly, and substituted sodium sulphate with a high water capacity absorbing industrial polymer. One gram of this polymer of acrylic acid (Aquapearl A3, Mitsubishi Chemical Industry Ltd, Tokyo, Japan) was reported to absorb 200 ml of water and was extremely cheap (around US $10/kg). Recoveries of 107 pesticides (from many different classes) from a wide variety of fruits and vegetables were > 70% and were generally in good agreement with recoveries using acetonitrile as the extraction solvent (with the exception of methamidophos, and possibly methidathion), as shown in Table 3.3.
85
S.L. Reynolds TABLE 3.3 Comparison of EtAc/polymer and MeCN in residue analysis [31] Sample
Pesticide
Lettuce Orange Pineapple Grapefruit Cucumber an
EtAc/polymer
Acetonitrile
Average result (mg/kg)a
RSD (%)
Average result (mg/kg)
RSD (%)
Permethrin Chlorpyrifos Triadimefon
0.06 0.12 0.50
2.7 15.1 5.2
0.07 0.13 0.51
10.7 1.8 6.5
Triadimefon
0.17
7.8
0.17
3.6
Methidathion Methamidophos
0.09 0.44
5.6 2.8
0.12 0.63
19.1 2.7
5.
3.6 3.6.1
FACTORS AFFECTING EXTRACTION EFFICIENCY pH
The pH of the extraction solvent can be extremely important for a number of pesticides, as it may not only affect their dissociation and salvation, but in some cases, also their stability. The pH of homogenates of fruits and vegetables varies widely, ranging from
o
00
P;
o
tc
CN
C
t x
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S.L. Reynolds TABLE 3.10 Summary of results from phases III and IV of the inter-comparison study for test materials containing incurred residues [62,63] Test material
Strawberry
Spinach
Carrot
Tomato
Apple
Wheat
Pesticide
Bupirimate Chlorpyrifos Dichlofluanid Iprodione Bifenthrin Dimethoate Metalaxyl Omethoate Permethrin Chlorfenvinphos Cypermethrin Dimethoate Metalaxyl Omethoate Triazophos Bupirimate Chlorothalonil Alpha endosulfan Beta endosulfan Endosulfan sulfate Tetradifon Tolylfluanid Bromopropylate Captan Fenoxycarb Phosalone Thiabendazole Chlorpyrifos-methyl Deltamethrin Lindane Permethrin Pirimiphos-methyl
Number of results
Mean result (mg/kg)
P
P1
R
P
P1
R
P
P1
R
6 7 7 7 7 6 5 7 7 6 3 2 3 0 6 7 6 7 8 8 7 6 7 8 6 8 8 8 8 8 8 8
9 9 8 9 8 9 7 8 9 9 7 4 7 1 9 9 8 7 8 8 8 8 8 8 9 8 9 8 8 8 8 8
11 13 11 13 12 13 9 11 12 14 4 2 7 2 14 13 12 13 13 13 10 12 12 12 12 13 14 13 13 13 12 13
0.56 0.21 0.11 1.32 0.72 0.26 0.03 0.14 3.67 1.59 0.03 0.04 0.03 0.83 0.15 0.27 0.08 0.15 0.18 0.02 0.08 2.14 1.77 0.33 3.21 3.16 3.21 0.75 0.20 0.73 3.63
0.53 0.21 0.11 1.53 0.77 0.27 0.03 0.09 4.25 1.69 0.02 0.02 0.03 0.01 0.84 0.16 0.36 0.11 0.15 0.18 0.01 0.08 2.31 1.73 0.33 3.35 2.64 3.26 0.84 0.22 0.85 3.80
0.52 0.17 0.10 1.29 0.69 0.25 0.03 0.19 4.00 1.36 0.02 0.02 0.03 0.03 0.63 0.15 0.36 0.09 0.17 0.20 0.01 0.09 2.42 1.75 0.32 3.28 3.69 2.84 0.78 0.19 0.78 3.23
18 16 40 9 13 16 15 46 32 13 85 52 4 17 15 40 43 20 16 28 14 14 13 16 12 56 17 22 30 17 18
23 10 8 12 9 12 10 42 19 14 60 26 10 12 14 33 11 30 27 21 26 12 11 10 10 58 12 17 21 14 12
20 14 9 17 13 18 27 35 14 19 26 2 17 74 23 15 26 35 21 19 32 24 14 26 13 11 50 27 22 31 19 29
CV (%)
Figures in bold type are outside criteria considered to be acceptable (Mean CV < 30%).
104
Sample handling and clean-up procedures I gas chromatographic equipment, any quantitative differences in the residue data were more likely to have been influenced by the individual practical skills and experience of each analyst, rather than any of the three extraction solvents.
3.9
OVERALL CONCLUSIONS
It seems likely that acetone, EtAc and MeCN will continue, at least for the foreseeable future, to be used to extract a wide range of chemical classes of pesticides from fruits and vegetables. SFE using liquid carbon dioxide has not proven to be an ideal replacement for organic solvents for fruits and vegetables, because of their high moisture content. The problems are twofold. First, so much desiccant is required that test portion sizes are very small and therefore the amount of pesticide available for determination will also be small. Secondly, with small test portions the sub-sampling error can be very large. Organic solvents will continue to be utilised but perhaps in conjunction with newer extraction technologies, such as pressurized liquid extraction and microwave extraction. Each of the three solvents has certain advantages/disadvantages when used as the primary extractant in MRMs, as have already been discussed in some detail in this chapter. The choice for the pesticide residue analyst remains difficult, and opinions as to which is the "best" extraction solvent for fruits and vegetables will remain divided. The best solvent is likely to continue to be determined much on the basis of the analyst's preference and particular requirements, rather than on results that can be used to differentiate their effectiveness. Also, with the exception of a few pesticide/commodities that are in the margins of being amenable to accurate quantification using multi-residue analysis, there is little difference between the solvents. If polar pesticides such as acephate, methamidophos, monocrotophos and omethoate must be determined then MRMs based on an EtAc extraction are most likely to yield higher recoveries, as there will be no necessity for a liquid-liquid partition step. Acceptable recoveries (> 70%) of these polar pesticides can be achieved by partition from acetone/water and MeCN/water into a non-water-miscible solvent, provided the predominantly aqueous phase is first saturated with a suitable salt such as sodium or magnesium sulphate. It must be stressed that the inter-comparison [56] and inter-laboratory [43] studies described in this chapter were only aimed at assessing "relative" extraction efficiencies. Determination of "absolute" extraction efficiency involves the application of radiolabelled pesticides, which is very costly 105
S.L. Reynolds and can be challenging. Previous studies [64,65] have demonstrated that pesticides can "bind" to food commodities of both plant and animal origins. Such residues may be either "bound" or "unextractable". Skidmore et al. [64] describes bound residues in the simplest terms as those residues that cannot be dissociated from the sample matrix by exhaustive extraction or digestion without changing their chemical nature. Matthews [65] reported that 28% of the applied dose of [1 4C] chlorpyrifos-methyl was unextractable from cereal grains using methanol after a prolonged storage period. However, when a 1:1 methanol/water mixture was used to extract the grains 86% of the radioactivity was released. It was postulated that the residue was retained due to physical entrapment, perhaps in the fibrous layers of the wheat grain and that the water/methanol mixture changed the matrix sufficiently to allow release. As a precaution against the possibility of this type of binding, participants in the inter-comparison study [56] were instructed to soak the wheat test material in water prior to the organic solvent extraction step (see section 3.8.1.3). GPC and HPGPC as clean-up techniques have the appeal of offering a broad range of applicability, both in terms of pesticides and commodities, and will continue to be used as a clean-up step in MRMs. However, the performance of alternative clean-up technologies and detection systems improves year by year. As automated, on-line clean up of sample extracts becomes more reliable and robust, and instruments such as triple-sector quadrupole mass spectrometers appear in more laboratories, so the use of a GPC/HPGPC clean-up step may decline. Nonetheless, there remains plenty of scope for further miniaturisation of this technology. REFERENCES 1 2
3 4 5
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Codex Alimentarius, Pesticide Residues in Food. Methods of Analysis and Sampling, 2nd ed., Vol. 2A, 2000, Part 1. Official Journal of the European Communities, Commission Directive 2002/63/ EC, Community methods of sampling for the official control of pesticide residues in and on products of plant and animal origin and repealing Directive 79/700/ EEC, 11 July 2002. FAO manual on the submission and evaluation of pesticide residue data for the evaluation of maximum residue levels in food and feed, Food and Agriculture Organisation of the United Nations, Rome, 1997. S.J.V. Young, C.H. Parfitt Jr., R.F. Newell and T.D. Spittler, Homogeneity of fruits and vegetables comminuted in a vertical cutter mixer, J. Assoc. Off. Anal. Chem. Int., 79(4) (1996) 976-980. PesticideAnalytical Manual, 3rd ed., Vol. 1, US Food and Drug Administration. Rockville, MD, 1994.
Sample handling and clean-up procedures I 6 7
8
9 10 11
12 13
14
15
16
17
18
19
20
21
S.F. Howard and G. Yip, Stability of metallic bisdithiocarbamates in chopped kale, J. Assoc. Off Anal. Chem., 54 (1971) 1371-1372. A.R.C. Hill, C.A. Harris and A.G. Warburton, Effects of sample processing on pesticide residues in fruit and vegetables. In: A. Fajgeli and A. Ambrus (Eds.), Special Publication No. 256, ISBN 0-85404-783-2, RSC, 2000. R.J. Fussell, A.K. Jackson, S.L. Reynolds and M.F. Wilson, Assessment of the stability of pesticides during cryogenic sample processing. 1. Apples, J. Agric. Food Chem., 50 (2002) 441-448. T.J. Bruno and P.D.N. Svoronos, CRC Handbook of Basic Tables for Chemical Analysis. CRC Press, Boca Raton, FL, 1989, p. 89. EH40/2002 Occupational Exposure Limits, HSE Books, Sudbury, Suffolk, UK, ISBN 0-7176-2083-2, 2002. F.J. Schenck and S.J. Lehotay, Does further clean-up reduce the matrix enhancement effect in gas chromatographic analysis of pesticide residues in food?, J. Chromatogr. A, 868 (2000) 51-61. P.A. Mills, J.H. Onley and R.A. Gaither, Rapid method for chlorinated pesticide residues in nonfatty foods, J. Assoc. Off. Anal. Chem., 46(2) (1963) 186-191. R.W. Storherr, P. Ott and R.R. Watts, A general method for organophosphorus pesticide residues in nonfatty foods, J. Assoc. Off. Anal. Chem., 54(3) (1971) 513-516. W.L. Ton Joe and W.G. Cusick, Multiresidue screening for fresh fruits and vegetables with gas chromatography/mass spectrometric detection, J. Assoc. Off. Anal. Chem., 74(3) (1991) 554-565. S.M. Lee, M.L. Papathakis, H.-M.C. Feng, G.F. Hunter and J.E. Carr, Multipesticide residue method for fruits and vegetables: California Department of Food and Agriculture, Fresenius J. Anal. Chem., 339 (1991) 376-383. J. Fillion, R. Hindle, M. Lacroix and J. Selwyn, Multiresidue determination of pesticides in fruit and vegetables by gas chromatography-mass-selective detection and liquid chromatography with fluorescence detection, J. AOAC Int., 78(5) (1995) 1252-1266. J. Cook, M.P. Beckett, B. Reliford, W. Hammock and M. Engel, Multiresidue analysis of pesticides in fresh fruits and vegetables using procedures developed by the Florida Department of Agriculture and Consumer Services, J. AOAC Int., 82(6) (1999) 1419-1435. V.G. Becker, Gaschromatographische simultanbestimmung von chlorierten Kohlenwasserstoffen und phosphorsaureestern in pflanzlichem material, Dtsch. Lebensm. Rundsch., 4 (1971) 125-126. M.A. Luke, J.E. Froberg and H.T. Masumoto, Extraction and cleanup of organochlorine, organophosphate, organonitrogen, and hydrocarbon pesticides in produce for determination by gas-liquid chromatography, J. Assoc. Off. Anal. Chem., 58(5) (1975) 1020-1026. M.A. Luke, J.E. Froberg, G.M. Doose and H.T. Masumoto, Improved multiresidue gas chromatographic determination of organophosphorus, organonitrogen and organohalogen pesticides in produce, using flame photometric and electrolytic conductivity detectors, J. Assoc. Off. Anal. Chem., 64(5) (1981) 1187-1195. W. Specht and M. Tillkes, Gaschromatographische bestimmung von ruickstinden an pflanzenbehandlungsmitten nach clean-up fiber gel-chromatogrphie und
107
S.L. Reynolds
22
minikieselgel-saulen-chromatogrphie, 3. Mitt.: methode zur aufarbeitung von lebensmitteln und futtermitteln pflanzlicher und tierischer herkunft fir die multirtickstandsbestimmung lipoid- und wasser 1oslicher pflanzenbehandlungsmittel, FreseniusZ. Anal. Chem., 301 (1980) 300-307. A. Koinecke, R. Kreuzig, M. Bahadir, J. Siebers and H.G. Nolting, Investigations on the substitution of dichloromethane in pesticide residue analysis of plant
materials, Fresenius J. Anal. Chem., 349 (1994) 301-305. 23
24
25
26
27
28
29
30
31
32 33
34
108
W. Specht, S. Pelz and W. Gilsbach, Gas-chromatographic determination of pesticide residues after clean-up by gel-permeation chromatography and minisilica gel-column chromatography, FreseniusJ. Anal. Chem., 353 (1995) 183-190. J.A. Casanova, Use of solid-phase extraction disks for analysis of moderately polar and nonpolar pesticide in high-moisture foods, J. AOAC Int., 79(4) (1996) 936-940. K. Nordmeyer and H.-P. Their, Solid-phase extraction for replacing dichloromethane partitioning in pesticide multiresidue analysis, Z. Lebensm. Unters Forsch. A, 208 (1999) 259-263. K. Adou, W.R. Bontoyan and P.J. Sweeney, Multiresidue method for the analysis of pesticide residues in fruits and vegetables by accelerated solvent extraction and capillary gas chromatography, J. Agric. Food. Chem., 49(9) (2001) 4153-4160. R.R. Watts, R.W. Storherr, J.R. Pardue and T. Osgood, Charcoal column cleanup method for many organophosphorus pesticide residues in crop extracts, J. Assoc. Off Anal. Chem., 52(3) (1969) 522-526. A.H. Roos, A.J. Van Munsteren, F.M. Nab and L.G.M.Th. Tuinstra, Universal extraction/clean-up procedure for screening of pesticides by extraction with ethyl acetate and size-exclusion chromatography, Anal. Chim. Acta, 196 (1987) 95-102. A.R. Fernandez-Alba, A. Valverde, A. Agiiera and M. Contreras, Gas chromatographic determination of organochlorine and pyrethroid pesticides of horticultural concern, J. Chromatogr. A, 686 (1994) 263-274. D.M. Holstege, D.L. Scharberg, E.R. Tor, L.C. Hart and F.D. Galey, A rapid multiresidue screen for organophosphorus, organochlorine and N-methyl carbamate insecticides in plant and animal tissues, J. AOAC Int., 77(5) (1994) 1263-1274. H. Obana, K. Akutsu, M. Okihashi, S. Kakimoto and S. Hori, Multiresidue analysis of pesticides in vegetables and fruits using high capacity absorbent polymer for water, Analyst, 124 (1999) 1159-1165. C.D.S. Tomlin (Ed.), The Pesticide Manual, 12th ed., British Crop Protection Council, Surrey, UK, 2000. D.M. Gilvydis and S.M. Walters, Gas chromatographic determination of captan, folpet and captafol residues in tomatoes, cucumbers and apples using wide-bore capillary column: interlaboratory study, J. Assoc. Off. Anal. Chem., 74 (1991) 830-835. R. Carabias Martinez, E. Rodriguez Gonzalo, Ma.G. Gracia Jim6nez, C. Gracia Pinto, J.L. Prez Pav6n and J. Hernandez Mendez, Determination of the fungicides folpet, captan, and captafol by cloud-point preconcentration and high-performance liquid chromatography with electrochemical detection, J. Chromatogr.A, 754 (1996) 85-96.
Sample handling and clean-up procedures I 35
36 37
38
39 40
41
42 43
44
45
46
47
48
49 50
C. De la Colina, F. Sdnchez-Rasero, G. Dios, E. Romero and A. Pefia, Effect of storage on the recovery of different types of pesticides using a solid-phase extraction method, Analyst, 122 (1997) 7-11. David R. Lide (editor-in-chief) (Ed.), CRC Handbook of Chemistry and Physics, 83rd ed., CRC Press, Boca Raton, FL, 2002-2003. S.J. Lehotay, A.R. Lightfield, J.A. Harman-Fetcho and D.J. Donoghue, Analysis of eggs by direct sample introduction/gas chromatography/tandem mass spectrometry, J. Agric. Food. Chem., 49 (2001) 4589-4596. J.H. Ruzicka, J. Thomson, B.B. Wheals and N.F. Wood, The application of gel chromatography to the separation of pesticides. Part I. Organophosphorus pesticides, J. Chromatogr., 34 (1968) 14-20. Z. Masud, V. Batora and Kovai6ova, Gel filtration clean-up multi-residues of organophosphorus pesticides in rice, Pest. Sci., 4 (1973) 131-136. R.C. Tindle and D.L. Stalling, Apparatus for automated gel permeation cleanup for pesticide residue analysis, applications to fish lipids, Anal. Chem., 44(11) (1972) 1768-1773. D.L. Stalling, R.C. Tindle and J.L. Johnson, Cleanup of pesticide and polychlorinated biphenyl residues in fish extracts by gel permeation chromatography, Anal. Chem., 55(1) (1972) 32-38. Deutsche Forschungsgemeinschaft, Manual of Pesticide Residue Analysis, Cleanup Method 4, Vol. 1. VCH, Weinheim, 1987, pp. 65-69. A. Andersson and H. Palsheden, Comparison of the efficiency of different GLC multi-residue methods on crops containing pesticide residues, FrenseniusJ. Anal. Chem., 339 (1991) 365-367. M. Anastassiades and E. Scherbam, Multimethode zur bestimmung von pflanzenschutz- und oberflichenbehandlungsmittel-ruckstanden in zitrusfruchten mittels GC-MSD, Dtsch. Lebensm. Rundsch., 93(10) (1997) 316-327. A. Gelsomino, B. Petrovicova, S. Tiburtini, E. Magnani and M. Felici, Multiresidue analysis of pesticides in fruits and vegetables by gel permeation chromatography with electron-capture and mass spectrometric detection, J. Chromatogr. A, 782 (1997) 105-122. A. Sannino, M. Bandini and L. Bolzoni, Multiresidue determination of 19 fungicides in processed fruits and vegetables by capillary gas chromatography after gel permeation chromatography, J. Assoc. Off. Anal. Chem. Int., 82(5) (1999) 1229-1238. J.A. Van Rhijn and L.G.M.Th. Tuinstra, Miniaturisation of size-exclusion chromatography as a powerful clean-up tool in residue analysis, J. Chromatogr., 552 (1991) 517-526. Analytical methods for pesticide residues in foodstuffs. In: P. van Zoonen (Ed.), General Inspectoratefor Health Protection, 6th ed., Rijksinstituut voor Volksgezondheid en Milieu (RIVM), Bilthoven, The Netherlands, 1996. H.B. Christensen and K. Granby, Method validation for strobilurin fungicides in cereals and fruit, FAC, 18(10) (2001) 866-874. D.A. Rimmer, P.D. Johnson and R.H. Brown, Determination of phenoxy acid herbicides in vegetation, utilising high-resolution gel permeation chromatographic clean-up and methylation with trimethylsilyldiazomethane
109
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51
52
53
54
55
56
57
58 59
60
61 62
63
110
prior to gas chromatographic analysis with mass-selective detection, J. Chromatogr.A, 755 (1996) 245-250. P.D. Johnson, D.A. Rimmer and R.H. Brown, Adaption and application of a multiresidue method for the determination of a range of pesticides, including phenoxy acid herbicides in vegetation, based on high-resolution gel permeation chromatographic clean-up and gas chromatographic analysis with mass-selective detection, J. Chromatogr. A, 765 (1997) 3-11. K. Mastovskd, J. Hajglovd, M. Godula, J. KiivAnkovd and V. Kocourek, Fast temperature programming in routine analysis of multiple pesticide residues in food matrices, J. Chromatogr.A, 907 (2001) 235-245. L.D. Johnson, R.H. Waltz, J.P. Ussary and F.E. Kaiser, Automated gel permeation chromatographic cleanup of animal and plant extracts for pesticide residue determination, J. Assoc. Off. Anal. Chem., 59(1) (1976) 174-187. J. Hong, Y. Eo, J. Rhee and T. Kim, Simultaneous analysis of 25 pesticides in crops using gas chromatography and their identification by gas chromatography-mass spectrometry, J. Chromatogr., 639 (1993) 261-271. J. Tekel and S. Hatrik, Pesticide residue analyses of plant material by chromatographic methods: clean-up procedures and selective detectors, J. Chromatogr.A, 754 (1996) 397-410. S.L. Reynolds, R.J. Fussell and M. Caldow, An inter-laboratory study of two CEN multi-residue methods for use in the enforcement of maximum residue levels for pesticides in fruit, vegetables and grain within the European Union, Pest. Sci., 50 (1997) 164-166. CEN Non-fatty Foods-Multi-residue Methods for the Gas Chromatographic Determinationof Pesticide Residues-Part2: Methods for Extraction and Cleanup, EN 12393-2, European Committee for Standardisation, Brussels, 1998. J.C. Miller and J.N. Miller, Statistics for Analytical Chemistry, ISBN 0-13030990-7, 3rd ed., Ellis Horwood Ltd., Chichester, West Sussex, UK, 1993, p. 84. S.L. Reynolds, R.J. Fussell, M. Caldow, R. James, S. Nawaz, C. Ebden, D. Pedlington, T. Stijve and H. Diserens, IntercomparisonStudy of Two Multiresidue Methods for the Enforcement of EU MRLs for Pesticides in Fruit, Vegetables and Grain, Phase I Intercomparison Study of Pesticide Solutions, Report EUR 17870 EN, European Commission, Brussels, 1997. S.L. Reynolds, R.J. Fussell, M. Caldow, R. James, S. Nawaz, C. Ebden, D. Pedlington, T. Stijve and H. Diserens, IntercomparisonStudy of Two Multiresidue Methods for the Enforcement of EU MRLs for Pesticides in Fruit, Vegetables and Grain, Phase II IntercomparisonStudy of Spiked Test Materials, Report EUR 18639 EN, European Commission, Brussels, 1998. W.J. Youden and E.H. Steiner, Statistics Manual of the AOAC. Association of Analytical Chemists, Arlington, 1975. S.L. Reynolds, R.J. Fussell, M. Caldow, R. James, S. Nawaz, C. Ebden, S. Lovell and H. Diserens, Intercomparison Study of Two Multi-residue Methods for the Enforcement of EUMRLs for Pesticides in Fruit, Vegetables and Grain, Phase III IntercomparisonStudy of Test Materials Containing Incurred Residues, Report EUR 19306 EN, European Commission, Brussels, 2000. S.L. Reynolds, R.J. Fussell, M. Caldow, R. James, S. Nawaz, C. Edben, S. Lovell and H. Diserens, Intercomparison Study of Two Multi-residue Methods for the
Sample handling and clean-up procedures I
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Enforcement of EU MRLs for Pesticides in Fruit, Vegetables and Grain, Phase IV Intercomparison Study of Test Materials ContainingIncurred Residues, Report EUR 19443, European Commission, Brussels, 2001. M.W. Skidmore, G.D. Paulson, H.A. Kuiper, B. Ohlin and S. Reynolds, Bound xenobiotic residues in food commodities of plant and animal origin, Pure Appl. Chem., 70(7) (1998) 1423-1447. W.A. Matthews, An investigation of the non-solvent extractable residues of [14 C] chlorpyrifos-methyl in stored wheat, Pest. Sci., 31 (1991) 141-149.
111
Chapter4
Sample handling and clean-up procedures II new developments Michelangelo Anastassiades and Ellen Scherbaum
4.1
INTRODUCTION
Pesticide residue analysis plays an indispensable role in estimating the exposure of humans and the environment to pesticides in controlling the compliance of farmers to good agricultural practice rules, in facilitating regulatory decisions and trading and in strengthening the consumers' trust towards food safety. In official government programmes and the private sector alike, residue control is gaining importance and there is a growing pressure on laboratories to improve cost-effectiveness and analytical performance and to decrease sample turnaround times. To address these needs, instrument manufacturers and residue analysts around the world are continuously developing and implementing new analytical techniques and approaches with the aim of simplifying and speeding-up procedures, improving quality and the scope of analysis and reducing chemical consumption and manual labour. In pesticide residue analysis, analyte concentrations are generally too low and samples too complex to be analysed without preliminary sample preparation. Because measurements are typically made at low levels, background interference is a problem to be addressed. The main goal of sample preparation is therefore to provide a sample fraction, which is enriched in all analytes of interest and as free as possible from interfering matrix components that will certainly be present in the extract. Any analyte losses occurring here cannot be compensated for in the subsequent measurement steps. Thus, sample preparation is a crucial part of the whole analytical process. Sample preparation begins with sample processing and ends with the generation of the final extract used for instrumental analysis. In the extraction step, analyte traces are released from the sample material Comprehensive Analytical Chemistry XLIII Fernindez-Alba (Ed.) ( 2005 Elsevier B.V. All rights reserved
113
M. Anastassiades and E. Scherbaum and transferred into the extraction medium. This is followed by the removal of potentially interfering co-extractives (i.e., purification or clean-up). Traditional methodologies include numerous manual sample-handling steps such as filtration, volume transfers, column chromatography, evaporations and reconstitutions. This not only adds to the overall complexity of these methods but also makes them time-consuming and prone to systematic and random errors. For a long time, sample handling has therefore been considered as the bottleneck in residue analysis. Compared with the field of instrumental determinative analysis (injection, chromatographic separation, detection and data analysis), where technological advances in hardware, software and computing have resulted in sophisticated and highly automated analytical instruments, developments in sample preparation were significantly slower. There are a variety of reasons for this, including: (a) in many research facilities sample preparation has traditionally been considered as a low-tech process of little academic interest and thus little activity was devoted to how procedures could be improved, (b) major instrument manufacturers did not invest in the development of automated sample preparation techniques, leaving this niche to smaller companies, and (c) the complexity of natural matrices, which in many cases discourages more fundamental research. Since the early 1990s, however, as a result of rapidly rising labour costs, the growing demand for residue controls and the call for a reduction of chemical waste, this trend has begun to change and sample preparation turned from being an "unpleasant necessity" into an interesting and challenging research task and a focus for improving overall laboratory efficiency. Since then, numerous sample-preparation approaches focusing on simplification, automation and miniaturisation, as well as on coupling with chromatographic analysis, have been introduced. It is important to note that, in numerous cases, simplifying sample preparation has only been made feasible by the enormous advancements in the field of determinative analysis, including injection technology, chromatographic separation and, most importantly, sensitive and selective detection. Sample preparation includes a vast number of more or less time-and labour-intensive sample manipulation and liquid handling tasks such as homogenisation, weighing, pipetting, dilution, agitation, filtration, centrifugation, drying and evaporation. There have been important developments in each of these fields in recent years. Nevertheless, this chapter will mainly focus on techniques dealing with extraction, purification and enrichment of analytes, which are the most critical steps in analysis. The distinction between extraction and clean-up depends on the point of view and there is 114
Sample handling and clean-up procedures II-new developments often disagreement as to how these terms should be used. In this chapter, there will be no strict division between extraction and clean-up techniques, as in several other publications, because in most cases these analytical steps cannot be strictly distinguished as they both deal with a more or less selective separation or isolation of the target analytes from matrix components. Various novel approaches and techniques will be presented, describing the theory behind each technique, discussing some critical aspects in method development and compiling some representative applications. Each section concludes with a critical discussion on the possibilities and limitations of the various techniques with emphasis on multi-residue method (MRM) applicability. As regards the sample types, the focus is on the analysis of fruit and vegetable samples while high fat content matrices (e.g., of animal origin) and environmental substrates (e.g., water, soil, air) are only covered marginally. Headspace analysis and derivatisation reactions are not covered. At the end of this chapter, there is a discussion about the difficulties encountered and the considerations that have to be made in the process of implementing a new sample preparation technique in a laboratory. 4.2
SAMPLE PROCESSING AND HOMOGENISATION
Pesticide residues in biological samples are usually unequally distributed, not only from unit to unit but also within single units. Thus, before the analytical portion is taken (sub-sampling), intensive cutting, chopping, shredding and blending or grinding is necessary to reduce particle sizes and ensure a statistically well-mixed homogenate that can be used for checking the compliance of the entire laboratory sample with maximum residue limits (MRLs). A thorough comminution reduces the variability of results within replicate test portions and improves the accessibility and extractability of residues. In terms of produce, commodities with soft flesh and relatively hard peel, such as grapes and tomatoes, are especially problematic and require special attention during comminution to sufficiently reduce the size of the peel pieces, which may contain large amounts of non-systemic pesticides. In the past, little attention has been paid by the analytical community to the improvement of sample-processing procedures. This was surely related to the fact that traditional multi-residue methodologies [1-4] were employing relatively large sub-sample sizes (50-100 g) and were thus less prone to subsampling variations. To improve the extractability of residues, most of these "macro-MRMs" involved an additional comminution with special blending devices (e.g., Ultra-Turrax) during the initial extraction step to further break up the sample particles. Since the mid-1990s, with the introduction of novel 115
M. Anastassiades and E. Scherbaum
extraction techniques such as supercritical fluid extraction (SFE) and pressurized liquid extraction (PLE) that typically employ small sample sizes and with the emerging trend to miniaturise analytical procedures in general, the homogeneity aspect has become increasingly important. Many studies have been conducted since then to describe the influence of sample processing on the degree of homogeneity and to estimate the uncertainty as a function of the analytical portion size [5-9]. In general, the smaller the analytical portion, the larger the derived uncertainty. Today, the degree of standardisation as regards sample processing is still low compared with other steps in pesticide residue analysis and the procedures followed in the various laboratories vary significantly in terms of the equipment that is employed and the sample temperature during comminution. The comminution offrozen fruits and vegetables in the presence of dry ice (cryogenic processing), which usually results in a free-flowing powdery material, is nowadays generally accepted as the most effective, yet feasible, sample-processing procedure for pesticide residue analysis. Cryogenic processing leads to a significantly better degree of homogeneity, thus measurably improving the accuracy in replicate sample analysis [8-12]. Allmendinger et al. [9] have investigated the variability of sub-sampling of cryogenically-processed apples, grapes and tomatoes, when 2, 5, 10 or 20 g sub-samples are used for analysis. With the exception of the 2-g grape sub-samples, all other combinations gave acceptable variations (RSD in % at n = 5) ranging between 4.7 and 11.1%, which is, considering the variation resulting from the residual sample preparation and analysis steps, a highly acceptable value. Ambrus et al. [11] have further demonstrated that the homogeneity of the samples is substantially improved when an aliquot of the initially blended samples is further blended after adding some water to it, a procedure previously proposed by Kadenczki et al. [13]. Cryogenic processing not only enhances homogeneity but also pesticide stability. Recently, Fussell et al. [14] and El-Bidaoui et al. [15] have shown that processing at ambient temperatures can lead to considerable losses of susceptible pesticides and thus to substantially biased (underestimated) results. For some extremely labile pesticides, such as most dithiocarbamates, degradation during cryogenic processing is unavoidable so determination is performed by measuring the degradation products. The deceleration of chemical reactions when maintaining low temperatures during processing also decreases the decomposition of sample components and can reduce the number of potentially interfering compounds in the extracts. This is often observed in the case of onion samples where, compared with traditional comminution, liquid nitrogen treatment followed by grinding significantly 116
Sample handling and clean-up procedures II-new developments reduces the amount of interfering sulphur-containing compounds in the extracts (note: such compounds are for the most part glycosidically bound to sugar molecules and enzymatically released as soon as the onion cells are broken). On the other hand, the reduced particle size resulting from the more thorough comminution at frozen conditions also leads to a more exhaustive extraction of sample components. This has been shown in the case of grapes where, in traditional processing, the seeds remain mostly intact while, in cryogenic processing, they are crushed to expose their content (e.g., oils and phenolic compounds) to the extraction solvent. In a broader sense, sample preparation also entails all the sampling steps performed outside the laboratory and many agree that the variabilities derived from this process often affect the analytical result more than any other part of the analytical procedure. The way sampling should be performed when controlling the MRL conformity ofcommodities is prescribed in several national and international guidelines that define the minimum number of units and sample amounts required. These sampling procedures have been developed with practicability in mind and do not necessarily ensure that the sample taken fully represents the whole lot. In recent years, there has been a growing interest in studying the unit-to-unit variability within composite samples [16,17], mainly in relation to the need to establish suitable models for the assessment of acute risks from pesticide intake through food consumption. 4.3
RECENT ADVANCEMENTS IN TRADITIONAL MRMs
Extractions with organic solvents followed by liquid-liquid partitioning (LLP) steps for clean-up purposes have been the standard techniques in residue analysis for a very long time and are still commonly used today. The main advantages over many newer approaches include the fact that they are based on familiar and established principles, that no expensive or complicated instruments are needed and that organic solvents of high purity are easily available, although at a relatively high price. Today, the most commonly used MRMs for the analysis of pesticides in fruits and vegetables involve initial extraction with acetone [3,4,18,19], acetonitrile [1,2,20-23], or ethyl acetate [24-29] followed by LLP, during which the analytes of interest are transferred into the organic layer, leaving unwanted hydrophilic co-extractives as well as some highly polar pesticides in the aqueous phase. When employing ethyl acetate, which is quite hydrophobic, the formation of a separate organic layer occurs readily. In the case of acetonitrile and acetone, however, which are highly water-miscible, phase separation requires the addition of non-polar organic solvents and/or salts. The types and amounts of the solvents and salts 117
M. Anastassiades and E. Scherbaum employed decisively influence the partitioning of compounds and consequently the selectivity of the methods. Following LLP, further purification usually involves one or more clean-up steps such as size-exclusion chromatography (SEC) or adsorption chromatography using normal-or reversed-phase sorbents. Traditional sample-preparation approaches are often very laborious and troublesome and have thus often been considered as the bottleneck steps in pesticide residue analysis. Some of their most typical practical disadvantages are: (a) the need to perform numerous labour-intensive and error-prone samplehandling steps (blending, evaporations, drying, phase separations, etc.), (b) the use of large volumes of toxic and inflammable solvents (high purchase costs, waste-disposal problems), (c) the extensive use of glassware items (and the associated dishwashing requirements and breakage losses) and (d) the need for laboratory fume hood and extensive storage and bench space. Furthermore, the analyte range covered by most traditional procedures is not broad enough to encompass important analytes. If at all, most laboratories cover such analytes using equally troublesome single-residue methods (SRMs) or moiety-specific (single-class) methods, the latter targeting multiple residues of chemicallyrelated pesticides. A great extent of the inefficiency and complexity of typical MRMs is related to their "macro" design, which leads to many of the aforementioned unnecessary drawbacks. Figure 4.1 summarizes some of the key factors contributing to the overall inefficiency of classical MRMs. MRMs have always been subject to numerous modifications aimed at improving analytical performance and clean-up efficiency, simplifying sample handling, achieving better amenability to automation and reducing solvent Main drawbacks
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M. Anastassiades and E. Scherbaum a method where 2-g vegetables are extracted with 3 ml acetonitrile, filtered, diluted with ammonium formiate buffer and injected (900 bl) onto an HPLC/ MS-MS system, achieving detection limits of 0.5-2 Ag/kg. Ingelse et al. [44] have directly analysed polar organophosphorous pesticides (that could not be satisfactorily recovered by traditional procedures using SPE) in water samples by directly injecting 1 ml into a HPLC/APCI-MS system equipped with a C18 polar end-capped column). Hyotylainen et al. [45] have presented a method where wine samples were directly injected onto an HPLC coupled on-line to a GC using a specially designed interface. The capabilities offered by large volume injection (LVI) in GC were exploited by Forcada et al. [46]. They developed a method where pesticides were extracted from 10 ml water into 1 ml of MTBE after addition of NaCl. 50 .ldof the extract were injected into the GC using a PTV. The whole procedure was performed in an automated fashion using a contemporary sample-preparation and auto-sampling station. A recently published MRM that takes advantage of the enhanced possibilities offered by modern analytical instrumentation is the QuEChERS method (see Fig. 4.2), which was designed to deliver extracts that are directly applicable to both GC and HPLC analysis. During the development of this method, great emphasis was put on streamlining the procedure wherever "QuEChERS" -eth: i(0 miL OTEE-tub (ph-adjust t if
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Sample handling and clean-up procedures II-new developments possible by simplifying or omitting impractical, laborious and time-consuming steps. The method involves initial extraction with acetonitrile, LLP after addition of a mixture of MgSO 4 and NaCl, which removes a significant amount of polar matrix components, followed by a simple clean-up step in which the extract is mixed with bulk SPE sorbent ("dispersive SPE") [52]. The advantages of this method include: (a) rapidity (sample preparation of eight previously homogenised samples in ca. 30 min), (b) simplicity, (c) reliability and robustness (few, simple steps), (d) low costs, (e) low solvent consumption (only 10 ml acetonitrile), (f) practically no glassware needs, (g) amenability of acetonitrile extracts to GC and LC applications alike and (h) coverage of a very broad pesticide spectrum (including basic, acidic and very polar pesticides). Excellent recoveries and low variations have been achieved in intralaboratory validation experiments [20]. The most important simplifications introduced in this method are shown in Table 4.2. These developments show that, despite the introduction of novel and highly sophisticated extraction and TABLE 4.2 Simple alternatives to troublesome analytical steps in conventional MRMs [201 Time and material consuming, complicated or error-prone steps in traditional methods
How to simplify?
Sample processing/homogenisation Blending (e.g., with Ultra-Turrax) during initial extraction Filtration of matrix bulk Use of multiple glassware for extraction, filtration and partitioning
No way around this Shaking
Multiple partitioning steps Separation/transfer of entire extract Evaporation/reconstitution in smaller volumes
Classical SPE with columns and manifold
Centrifugation Extraction, partitioning and centrifugation are performed in a single vessel Single partitioning (on-line approach) Take aliquots (use ISTD if volume is not known) Use smaller amount of organic solvent to obtain a more concentrated end-extract (check extractability of incurred residues). Employ large volume injection and use sensitive and selective instruments for measurement Dispersive SPE
123
M. Anastassiades and E. Scherbaum clean-up approaches, LLP will most likely remain a viable approach in the foreseeable future. 4.4
4.4.1
EXTRACTION AND PARTITIONING ASSISTED BY SOLID SUPPORT MATERIALS Introduction
In view of certain drawbacks associated with traditional LLP procedures employing separatory funnels, alternative procedures have been developed that make use of adsorbents to disperse samples (or sample extracts) in order to facilitate extraction and/or LLP. These procedures may involve macroporous normal-phase adsorbents such as diatomaceous earth (see sections 4.4.2 and 4.4.3) or reversed-phase silicas (see section 4.4.4). In a typical procedure, samples are mixed with sorbents (e.g., using pestle and mortar) to form a flowing powder that is filled onto columns to be eluted with appropriate solvents. Alternatively, liquid samples or extracts may be poured directly into columns already filled with the sorbent. These procedures have several practical advantages including: (a) the mechanical grinding with the irregularly shaped sorbent particles destroys tissue structures and cells, releasing enclosed residues, (b) the dispersion of the samples over a large surface area facilitates analyte accessibility and partitioning, the sample gets loosened-up and is more easily penetrated by solvents without the need of applying too much pressure for elution, (c) water and solid matrix particles are physically retained and (d) depending on the sample-sorbent combination, the sorbent may also act as a retentive, thus providing an additional selectivity potential. Compared with traditional extraction and partitioning approaches, the use of dispersing materials helps to avoid repetitive partitioning steps, troublesome separation of layers and potential formation of emulsions and filtrations. The approach is thus much more straightforward and more amenable to automation (see PLE and SFE in sections 4.5 and 4.7). 4.4.2 Dispersion of samples on macroporous normal-phase adsorbents In the extraction of biological samples, the use of solid support materials, such as diatomaceous earth, Celite, Florisil, silica gel and sea sand, has a long tradition. Having a surface which is highly wettable by water, such normal-phase adsorbents can disperse the sample water as a thin film over 124
Sample handling and clean-up procedures II-new developments a very large area, thus facilitating extraction and partitioning. This is usually performed by simply filling the sample sorbent mixtures into columns and eluting with organic solvents. Drying salts, such as NaSO 4 , have also frequently been used in combination with the above-mentioned sorbents to control sample moisture better. In some cases, various additional adsorbents such as alumina have been employed on-line in series to remove interferences from the eluted extracts. The concept of distributing aqueous samples over a large surface followed by LLP was already introduced for drug analysis in the mid 1970s. In pesticide residue analysis, the approach has traditionally been mainly employed for samples of animal origin such as milk and milk products, fish, meat, fat, etc. More recently, however, several applications for fruit and vegetable samples have been presented as well. Table 4.3 compiles some applications with emphasis on samples of plant origin. Owing to its simplicity, the approach has often been performed in automated or semi-automated fashion, as in the case of Soxhlet extractions and more recently in SFE and PLE, where Hydromatrix, cellulose and, more recently, synthetic polyacrylbased polymers are also employed. 4.4.3
Dispersion of extracts on support materials
The above-mentioned macroporous normal-phase support materials have not only been employed for the direct dispersion of pre-homogenised samples, but also for the dispersion of sample crude extracts previously generated using traditional methodologies. While the initial extraction is still performed as in traditional MRMs, the troublesome and time-consuming clean-up by LLP in separatory funnels is avoided. Typically, the crude sample extracts are filtered and an aliquot is poured into a column already containing the macroporous support material. In most applications, the organic solvent used for the initial extraction is fully or partially evaporated before or after the dispersion of the extracts onto the sorbent. In the latter case, the solvent is purged by passing a nitrogen stream through the column, thus leaving the support material covered by a thin aqueous layer (in the case offruit and vegetable extracts) or a thin film of fatty material (in the case of lipid extracts). In a process that essentially resembles both LLP and chromatography, the columns are then eluted with a relatively large amount of solvent that is preferably nonmiscible with the dispersed aqueous or fatty layer. This results in a more or less selective partitioning of the analytes into the eluting solvent. The required adsorbent columns can be manually prepared in the laboratory, but several manufacturers also offer ready-to-use disposable cartridges filled with macroporous adsorbents that can be used for this purpose. 125
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Sample handling and clean-up procedures II-new developments Table 4.4 shows some applications where this approach has been used to analyse pesticide residues. Podhorniak et al. [62] have dispersed crude fruit and vegetable extracts (acetone:water 2:1) on Hydromatrix filled in a column. Elution was performed with dichloromethane while Hydromatrix was re-used after a thorough cleaning procedure. However, total solvent consumption was even higher than in the Luke procedure [4] that was intended to be simplified. Di Muccio et al. [63] also used acetone:water 2:1 extracts and dispersed them on disposable Extrelut-20 columns. Before eluting with dichloromethane, acetone was partly removed. By purposely leaving excessive adsorbent (not wetted) at the bottom of the column, additional clean-up was achieved (the rest of the adsorbent was deactivated by the sample water, thus merely serving as a support in the partition process). Iijima et al. [64] dispersed crude acetone extracts of tomato on Chem-Elut diatomaceous earth adsorbent after previously removing most acetone by evaporation. The 49 selected analytes from various classes were sequentially eluted with hexane and ethylacetate followed by silica gel clean-up. Most analytes gave high recoveries except for the very polar acephate and some degradation-prone analytes. Low recoveries were also reported for highly non-polar pesticides such as pyrethroids, which obviously started precipitating following the evaporation of acetone and thus becoming inaccessible to the water-immiscible solvents employed for elution. In preliminary experiments without a real matrix, the authors observed a correlation between the log P,ow values of 171 pesticides and their elution behaviour during the partitioning on Chem-Elut and the silica clean-up. In a recent publication, Klein and Alder [421 describe a very fast and effective method that uses this partitioning concept for the isolation of pesticides amenable to HPLC analysis. Fruit and vegetables samples are initially extracted with methanol (water:methanol 1:2) and an aliquot of this extract is dispersed on Chem-Elut cartridges after the addition of salt. Elution/ partitioning is performed with dichloromethane. After solvent exchange to water/methanol, the extracts are directly analysed by HPLC -MS/MS without any additional clean-up. A different type of water-adsorbing material based on polyacryl was used by Obana et al. [65] who poured ethyl acetate extracts of fruits and vegetables into a column containing the polymeric adsorbent as well as carbon for clean-up. In an earlier study [66], the water absorbent was directly added to the sample before extracting with ethyl acetate. Argauer et al. [67] have analysed carbamate insecticides in meat by distributing an aliquot of the concentrated acetonitrile extracts on Hydromatrix that was filled in a SFE thimble to be re-extracted by supercritical CO 2 . This resulted in an additional discrimination of matrix co-extractives.
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Matrix solid phase dispersion (MSPD)
Instead of mixing the samples with normal-phase dispersing materials, as described above, MSPD uses reversed phase silica-based sorbents. The concept was introduced in the late 1980s by Barker et al. to simplify sample preparation of high fat content matrices. Meanwhile, however, it is also widely employed for the analysis of pesticides in fruits and vegetables. MSPD applications involve direct blending of a small sample amount (e.g., 0.5 g) with bulk RP-silica-based sorbent to form a semi-dry, free-flowing powder that can be filled into columns to be eluted with small solvent volumes (Fig. 4.3). Grinding is usually performed with a pestle in a mortar, while syringe barrels are often employed as reservoirs, using the syringe plunger for placing a frit on the top of the bed, for compressing the sample and for applying positive pressure during elution if necessary. Some authors recommend washing and pre-conditioning of the RP-sorbent prior to blending with the sample to remove potential interferences and improve wettability and thus facilitate interactions with the matrix [71]. During grinding, the sorbent acts as an abrasive to destroy tissue structures, thus improving the accessibility and extractability of enclosed residues. This is very important in the case of animal tissue samples that often contain proteins, lipids and sturdy conjunctive
Sorbent
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129
M. Anastassiades and E. Scherbaum tissue. When samples of high fat content are processed, the lipid material is dispersed as a thin film over the lipophilic RP-surface, which not only facilitates the extraction process but also instigates an additional clean-up effect. In a way, MSPD is a form of chromatography, the general principles of which apply. However, the whole process is very difficult to predict because the sample forms part of the chromatographic system and because analytes are dispersed throughout the sorbent-matrix mixture rather than being concentrated at the top of the bed as in typical chromatographic procedures. The efficiencies of extraction and clean-up, which are performed simultaneously, greatly depend on the dynamic interactions between the dispersed matrix, the sorbent, the elution solvent and the analytes. Additional adsorptive materials are often placed on-line in series to the MSPD column to remove further coextractives. To facilitate this process, dual-compartment cartridges have recently been introduced, where the adsorbent/matrix-mixture can be filled in the upper compartment while the lower compartment, which is separated by a frit, can contain a clean-up sorbent or drying salt of choice. To further optimise clean-up, several authors have performed fractional elutions, initially using extraction conditions that retain the analytes and remove interfering matrix components (inverse extraction) followed by conditions where the analytes are eluted. In many cases, direct analysis of the collected extracts, without any additional clean-up, was reported. MSPD is a very straightforward and simple extraction technique that requires neither sophisticated and expensive apparatus nor extensive amounts of materials and solvents and is thus more economical and faster than many traditional approaches. The elution procedure is potentially amenable to automated sequential processing using robotics and on-line hyphenation with chromatographic determination. However, care should be taken to avoid degradation of analytes while samples are awaiting analysis. The very small sample size (0.1-2 g) employed in MSPD can be an advantage if limited sample is available but, in most cases, it is a decisive disadvantage because of the difficulties associated with achieving the degree of homogenisation that is necessary to ensure that such a small sub-sample is representative of the initial laboratory sample. In general, the sample size in MSPD is limited by the cost of the sorbent and the fact that large bed sizes may cause high backpressures and plugging. It is thus generally not recommended to use sorbents with particle sizes smaller than 40 gm [71]. A practical difficulty of MSPD is the quantitative transfer of the sample into the reservoir, which requires rinsing mortar and pestle with the elution solvent.
130
Sample handling and clean-up procedures II-new developments Applications: A vast number of analytical methods involving MSPD have been published to date. Initially, the primary interest has been in the analysis of drugs and their metabolites as well as toxic pollutants in animal tissues, but the number of pesticide residue applications is meanwhile rapidly increasing. Several reviews summarise the use of MSPD in the analysis of animal tissue samples [72,731 and food in general [741. Valuable information about how to develop MSPD methodologies is presented in Ref. [71]. As shown in Table 4.5, most MSPD applications for fruit and vegetables employ Cs or C1 s sorbents at a sample/adsorbent ratio of 1:1. Several methods involve post-elution clean-up with normal-phase adsorbents, while fractional elution (e.g. washing step prior to the elution of analytes) has only been occasionally used. Automated elution has been accomplished by Kristenson et al. [801, who miniaturized the approach using a very small aliquot of the sample/adsorbent mixture equivalent to only a 25-mg sample. The aliquot was filled into a stainless steel vessel that was connected to an automated pumping system for pre-washing and analyte elution into a micro-vial for GC/MS analysis. 4.5 4.5.1
PRESSURIZED LIQUID EXTRACTION (PLE) Introduction
PLE is an automated extraction technique that uses heat to take advantage of the faster analyte kinetics at elevated temperatures, thus achieving fast extractions with relatively small amounts of solvents. In order to keep the solvent in a liquid state and enable safe instrument operation, pressure is applied on the extraction cell using a pump. The approach was developed in the mid-1990s following the introduction of automated SFE at a period of growing interest for extraction techniques that reduce solvent consumption and manual work. Depending on the author or instrument manufacturer, the technique has been also referred to as pressurized fluid extraction (PFE), pressurized solvent extraction (PSE), enhanced solvent extraction (ESE) and accelerated solvent extraction (ASE), the latter being the registered name of the most prominent PLE instrument manufacturer. A typical ASE instrument set-up is shown in Fig. 4.4. 4.5.2
Analytical procedure and critical parameters
In a typical procedure, the sample is packed into a special pressurisable vessel, which is placed in a carousel to be sequentially extracted without 131
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Fig. 4.4. PLE instrumentation, scheme [84]. operator attendance. In many cases, it is necessary to mix the samples with supporting materials such as sand, diatomaceous earth and Hydromatrix to control moisture or to avoid agglomeration of the sample and ensure unhindered and uniform solvent flow. The development of PLE methods is usually quite straightforward and simple because of the few experimental parameters involved and because the principle of extraction is more or less familiar to analysts having previous experience with traditional extraction/ partitioning procedures and column chromatography. Besides the sample type, the most important parameters to be considered in PLE applications are: (1) solvent type, (2) temperature, (3) extraction time, (4) number of extraction cycles, and (5) pressure. Solvent type: The selectivity and efficiency of PLE extractions is primarily controlled by the choice of solvent. In general, solvents typically used in conventional extraction approaches also work well in PLE. It should always be considered, however, that the properties of solvents, including polarity and miscibility, can alter considerably at different temperatures. Unfortunately, the physicochemical properties of many common solvents are not yet known well enough at the elevated temperatures (and pressures) employed in PLE. Temperature: Increased temperature enhances the solubility of analytes, promotes their diffusion within the matrix and accelerates their desorption kinetics by weakening various inter-molecular forces between them and active sites on the matrix surface, such as hydrogen bonds and dipole-dipole
133
M. Anastassiades and E. Scherbaum
attractions. The viscosity and the surface tension of the solvents are reduced, thereby increasing their ability to "wet" and penetrate the matrix and solubilise the target analytes. In general, raising the temperature reduces selectivity by increasing the extraction of matrix components and thus cleanup is often necessary prior to chromatographic analysis. Because of elevated temperatures, possible thermal degradation of susceptible analytes should always be explored in PLE applications. Increasing losses of dichlofluanid, captan and folpet, which are known to be sensitive to hydrolysis, have been observed during extraction from various samples as extraction temperatures were increased from 80 to 140°C [85]. Okihashi et al. [86] investigated the behaviour of N-methyl-carbamates during PLE at 100°C without noticing any degradation. It should be noted that drying salts such as Na 2SO 4 and MgSO 4, which have been successfully employed in many SFE applications, lose much of their ability to entrap molecular water as temperature increases. In addition, hydrated MgSO 4 tends to melt at elevated temperatures and is thus not recommendable. Good water-binding capacities at elevated temperatures have lately been observed for polyacryl-based drying polymers. Cycles: Extraction is performed in static cycles (typically 5 min). The dynamic extraction in PLE is quite negligible compared to SFE (see section 4.7), merely comprising a simple flushing out of the solvent into the collection vessel using additional solvent (between two extractions) or an inert gas (after the last static extraction). Several static cycles have been proven to be useful in the case of very high analyte concentrations or when matrices are difficult to penetrate. When low-temperature extractions are necessary to avoid degradation of analytes, extraction kinetics are less favourable, so multiple static cycles may be necessary to obtain higher recoveries. Pressure: In PLE applications, the pressures applied are typically far higher than needed to maintain the solvents (which are usually heated at temperatures exceeding their atmospheric boiling points) in the liquid state. Changing the pressure will normally have very little impact on analyte recovery; however, high pressure is claimed to force the solvents into areas that would be inaccessible under normal elution conditions such as small pores sealed by air bubbles. Sample type: As described in section 4.4, wet samples have to be mixed with adsorbents to control water and distribute the matrix over a large surface so that analyte transfer to the extraction solvent is facilitated. In the case of very non-polar analytes, a thick water film may act as a barrier that prevents non-polar solvents from reaching the analytes. In this case, the use of polar
134
Sample handling and clean-up procedures II--new developments co-solvents can assist the extraction and this may result in a higher content of water and polar co-extractives in the final extracts. Extractions at higher temperatures will also facilitate the analyte transfer to the extraction solvent, but this raises the potential for analyte degradation. Low-humidity samples can be applied to PLE as such, but particle size should be small enough to allow fast extraction. The use of support materials such as sand, cellulose or glass balls can help to prevent clogging and facilitate elution if necessary. In many cases, the addition of water to the samples will enhance the recoveries of analytes (especially the most polar ones), since water weakens polar analytematrix interactions such as hydrogen bonds. Following the extraction of fruits and vegetables, all authors report the presence of water in the collection vial. This water was either removed by adding a drying salt directly to the collection vial [85] or, more inconveniently, by LLP after addition of non-polar solvents and salting out. 4.5.3
Published applications
Remarkably soon after its introduction, PLE has become established in environmental laboratories. Helpful in improving the acceptance of PLE was the fact that the approach is comparable with traditional solvent-based procedures and that instrument manufacturers have actively pursued the establishment of an official EPA method for various contaminants and residues in soil. In many environmental laboratories, the introduction of PLE resulted in a drastic reduction of extraction times for soil and solid waste samples from hours (Soxhlet) to minutes [87-91]. The adoption of PLE in routine pesticide residue analysis of food was not that fast. Some PLE applications for pesticide residues in food are listed in Table 4.6. In Italy and Germany, ASE procedures have already gained official status for the analysis of fruit and vegetables and plant material with low water content [92,93]. In a recent application, Korta et al. [94] have employed PLE to extract six acaricides from honey that was previously dispersed on diatomaceous earth using a mixture of hexane:propanol for extraction. In general, PLE can achieve high recoveries for most pesticides in food matrices; however, extraction selectivity tends to be lower compared with traditional extraction methods and much lower compared with SFE. In most applications, instrument conditions during extraction vary between 60 and 120°C and 80 and 150 bar and typical extraction times range between 10 and 20 min. Total sample processing is, however, longer due to the need for mixing the sample with adsorbent, filling the vessel, post-extraction water removal, clean-up and evaporation prior to chromatographic analysis. 135
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M. Anastassiades and E. Scherbaum the activity of residual silanol groups on the surface of RP-modified silicas. In early days, silicas were generated from natural diatomaceous earth material employing special sol-gel processes and were generally characterised by a high content of metal impurities (e.g., Fe and Al). After discovering that the presence of these metals within the silica structure enhances the acidity (and thus activity) of neighbouring silanol groups, great efforts have been undertaken to improve the silica purity. The problem has finally been successfully addressed by introducing the so-called "ultra-pure" silicas, which are synthesized from tetraethoxysilan (TEOS), allowing the production RP sorbents with silanol groups of low acidity. A reduction of the number of residual silanols has been also accomplished by performing the alkyl bonding with tri-functional silanes (e.g., trichloroctadecylsilane), which can simultaneously react with neighbouring silanol groups. Residual silanol groups are then covered by endcapping with small-sized silanes (e.g., trimethylchlorosilane). This trend of producing end-capped sorbents for HPLC was initially also followed in SPE; however, this began to change after the usefulness of such silanol groups in providing additional (secondary) interactions and in enhancing the sorbent wettability, which is very important in the extraction of aqueous samples, was understood. So, various manufacturers began to reintroduce C18 sorbents with unmodified silanol groups, prepared either by modifying silicas with monofunctional alkylsilanes or by keeping the alkyl chain saturation low (low carbon loading). Some common descriptions for such sorbents are C18/OH, C18-light or polar-C18. Nevertheless, despite the great efforts to improve the retention of polar analytes (pKo < 1.5) from aqueous samples, alkyl-silicas are still not strong enough and are thus rarely used for multi-residue analysis of water samples when polar pesticides are to be included. Another limitation of bonded silicas is the narrow pH stability range. Below pH 2, the silyl bond can be hydrolysed while above pH 8 the silica base is liable to dissolution. This, however, is rarely a problem in practice as elution times in SPE tend to be short and the columns are intended for single use. Polymeric sorbents: The use of polymeric resins in SPE-like procedures is not new. Highly hydrophobic resins based on polystyrene divinyl benzene (PS-DVB) such as the Amberlite XADs have been used since the late 1960s for the extraction of contaminants from water samples. The retentive power of these polymeric adsorbents is based on a combination of hydrophobic mechanisms and l-II interactions. The retention capabilities of these early PS-DVB resins towards polar analytes were typically higher than of C18 silicas, but still not strong enough to meet the needs of multi-residue analysis, mainly because of the relatively low surface areas of these sorbents (e.g., 300 m 2/g for XAD-2 and 500 m2 /g for PLRP-S). The inadequacy of alkyl-silicas 174
Sample handling and clean-up procedures II-new developments and early polymeric sorbents to address the problem of sufficient retention of polar pesticides from large-volume water samples has led to the development of highly cross-linked PS-DVB resins that are characterised by a higher porosity and a larger specific surface area (700-1200 m2 /g). This translates into higher sorptive capacities and significantly larger breakthrough volumes, as confirmed in numerous studies [210,211]. A study has shown that highly cross-linked polymers can even retain ionic analytes from water samples due to the strong interactions with the lipophilic part of the molecules [2101. Many authors have reported that, compared with alkyl-silicas, polymeric resins give extracts containing more polar matrix interferences. These can be discriminated by adding a small amount of an organic solvent directly to the sample before extraction and/or subsequent to the washing solution. This is, of course, only feasible when the targeted analytes are better retained (less polar) than the interferences. This approach is also beneficial in the analysis of highly nonpolar pesticides such as pyrethroids and organochlorine compounds, which are notorious for their tendency to precipitate on containers and tubes [2121. A parallel development to the highly cross-linked PS-DVB is that of the functionalized polymeric resins. Several types of functional groups have been introduced to various types of PS-DVB polymers, including acetyl, hydroxymethyl, sulfonyl, o-carboxybenzoyl, and benzoyl [205,213,214]. This functionalization improves the contact with aqueous samples and several studies have shown that the recoveries of polar analytes are higher than those obtained by the unmodified analogues. An alternative type of such polymers is generated by co-polymerization with polar monomers such as N-vinylpyrrolidone (NVP). Such a co-polymer is the patented Oasis HLB (Waters) that is claimed to possess an excellent water wettability and not to require pre-conditioning with bipolar solvents as is the case with reversed-phase silica and unmodified PS-DVB sorbents. It is also reported that drying out of the sorbent during the extraction procedure does not diminish its ability to retain analytes. Owing to its relatively large surface area of 800 m2 /g and the hydrogen acceptor properties of the pyrrolidone group, the sorbent furthermore has an excellent retentive power. Other sorbent producers, meanwhile, also offer polymeric sorbents combining high specific area with polar groups such as Abselut NEXUS (Varian), Strata X (Phenomenex), H 2 0-philic DVB (JT Baker) and ENV + (IST). Most of these are of undisclosed chemical structure. A recent development, mainly driven by the needs of drug analysis, are the so-called mixed-mode polymeric sorbents that contain lipophilic (e.g., C8, C18) and ionic (e.g., sulfonic acid, carboxylic acid, diethylenetriamine) groups attached to the same polymeric PS-DVB backbone. Mixed-mode sorbents can 175
M. Anastassiades and E. Scherbaum retain compounds by both reversed-phase and ionic mechanisms and can thus be used to efficiently separate them from both non-ionic and permanently ionic interferences. This is achieved by properly adjusting the composition (pH, polarity) of the mobile phase during the extraction, washing and elution steps. Of great importance is the possibility to eliminate inorganic ions, which often pose a competition problem in ion-exchange chromatography and suppress signals in LC/MS applications. This principle was used by Young et al. [215,216] to isolate thiabendazole and carbendazim from juices, using a mixed-mode polymeric sorbent (Oasis MCX). Prior to the introduction of mixed-mode sorbents, such separation strategies were performed using two types of sorbents, which were either contained in one cartridge (as disks or sorbent beds) or in two separate cartridges sequentially arranged (tandem cartridges) [2171. The recent advances in the field of polymeric adsorbents have opened new horizons for pesticide residue analysis. Due to the higher capacity and retention power (especially for polar analytes), smaller bed volumes can be employed to achieve the same retention capabilities, which translates in higher flow rates and reduced clogging problems. Highly cross-linked PS-DVB sorbents have meanwhile replaced silica-based sorbents for the extraction of water samples and it can be expected that many more polymeric sorbents with various functionalities will be introduced in the future. In on-line SPE-HPLC applications, due to the fact that polymeric sorbents are more retentive than the silica-based ones that are contained in the analytical columns, special elution strategies are required to avoid band broadening, such as columnswitching, backflush elution and eluent dilution prior to entering the analytical column. The low-pressure resistance of polymeric sorbents should also be considered. Carbon-basedadsorbents:These sorbents occupy a special place because of their unique retention properties. In the past, carbon was notorious among chemists due to the great number of charcoal types and the irreproducibility of applications. The situation dramatically improved with the introduction of graphitised carbon blacks (GCBs), which are obtained from heating carbon blacks at 2700-3000°C in an inert atmosphere. These are essentially nonporous sorbents with a surface area of about 100 m 2/g, consisting of hyphenated hexagonal rings in graphitic layers held together by dispersive forces. Analytes are retained via 7r-ir- and hydrophobic interaction mechanisms, strongly depending on their structure and less on the presence of functional groups. Strong retention is usually obtained for planar molecules containing delocalized electronic bonds and hydrocarbons with potential for multiple surface contact points. Positively-charged chemical heterogeneities on their surface give carbon-based sorbents an additional anion-exchange 176
Sample handling and clean-up procedures II-new developments character, which has even been used to fractionate acidic pesticides from neutral and basic ones [218]. Carbons can be run in reversed-phase or normalphase applications. RP mechanisms contribute to, but do not rule, the retention. The complex interaction mechanisms, however, make it difficult to predict the retention. Newer Carbograph sorbents have surfaces greater than 200 m2 /g and have been reported to provide better recoveries of certain polar pesticides than highly cross-linked polymers. A drawback of carbon-based sorbents in general is their excessive, even irreversible, retention of certain analytes that complicates elution [77]. Typical SPE elution solvents such as acetonitrile and methanol are sometimes too weak, so methylene chloride, toluene or tetrahydrofuran has to be used to disrupt the interactions. Another drawback is the poor mechanical stability (pressure resistance) of carbon sorbents, which makes them inappropriate as HPLC column materials. Inorganic normal-phase adsorbents: Normal-phase (NP) adsorbents have been widely used for several decades for the clean-up of extracts in a procedure described as column extraction or liquid-solid partitioning (LSP). Normalphase sorbents show their highest retentive power in aprotic media of low dielectric constant such as non-polar organic solvents and are thus mainly used for the clean-up of sample extracts dissolved in such solvents (e.g., hexane, isooctane). Elution sequences with solvent mixtures of increasing polarity allow a separation into fractions on the basis of polarity. In traditional MRMs, NP chromatographic clean-up was performed using alumina, Florisil or silica columns (sometimes mixed with charcoal) prepared by the analyst in the laboratory. The poor batch-to-batch reproducibility of the sorbents, their need for deactivation and partial reactivation and the troublesome manual column preparation led to rather time-consuming procedures and variable results. Nowadays, NP-sorbents can be purchased in disposable cartridges. NP materials are usually intended for single use, since many of the polar co-extractants bind firmly to their surface and are difficult to remove. The fractional elution typically starts with a highly non-polar solvent, which elutes very non-polar pesticides (e.g., organochlorine compounds), thus separating them from the more polar triglyceride fraction. The elution continues with solvent mixtures of increasing polarity, allowing the displacement of more and more polar pesticides [3]. In a multi-residue approach, however, the plethora of pesticides of interest usually cover a very broad polarity range, making a clear separation between individual groups impossible. In principle, this procedure merely splits pesticides and matrix components into different fractions based on their polarity. NP clean-up is thus often performed following GPC clean-up that complementarily removes fat and pigments on the basis of the molecular-size-exclusion principle. 177
M. Anastassiades and E. Scherbaum Probably the most decisive drawback of fractional clean-up is that the different fractions have to be handled and injected separately, which translates into more manual and administrative work. Losses for certain polar pesticides have been reported by various authors. There are numerous applications where NP adsorbents were applied in pesticide residue analysis. While, in the early days, large amounts of sorbents were used, e.g., 20-40 g, newer applications employ miniaturized self-made or commercial columns filled with, for example, 0.5-2 g sorbents [3,219]. Restricted access materials (RAMs): RAMs are dual-coated, silica-based
sorbents with controlled small pores. The sorbent surface within the pores (inner surface) is modified with groups that allow retention of analytes through hydrophobic, ionic or affinity interactions while the external surface is modified with hydrophilic moieties that are non-retentive when aqueous samples are injected. Such sorbents are also described as internal surface reversed-phase (ISRP) materials. Owing to the small pore diameter, only analytes with a low molecular weight have access to the retentive sites while macromolecular matrix components remain in the void volume and can be directly flushed into the waste. Thus, in principle, RAM combines size exclusion of high-molecular-mass matrix components with the simultaneous adsorptive enrichment of low-molecular-mass analytes. RAMs are almost exclusively used as pre-columns in on-line SPE-LC systems with column switching arrangements that allow direct injection of biological and environmental samples containing macromolecular components such as proteins and humic acids. A typical procedure starts with trace enrichment of the analytes on the RAM pre-column and at the same time the separation of macromolecular compounds followed by the elution of the analytes into the analytical column and the regeneration of the RAM column in the backflush mode. One of the main advantages of using RAMs on-line to HPLC is the protection of the analytical column from being contaminated by large bio-polymers. Such compounds tend to precipitate on the column surface and block the access of analytes to the adsorptive sites. Furthermore, they may modify the retention properties of the sorbent and increase the backpressure during elution. The most popular RAMs are the alkyl diol silicas (ADS), which are diol-modified silicas with an internal pore surface modified with lipophilic alkyl groups (C 18, C8, C4). 4.9.1.6 Formats
The developments in SPE technology not only concern the available sorbents but also the different formats designed to provide better handling, 178
Sample handling and clean-up procedures II-new developments performance and automation possibilities. While in the 1960s adsorption chromatography was merely performed in laboratory-filled glass columns, today there is a great variety of pre-packed, disposable SPE formats to choose from, ranging from simple packed syringes and cartridges to disks, 96-well plates and SPE pipette tips. The traditional cartridge (previously syringe barrel) is still the most popular SPE format. Disposable SPE cartridges, as we know them today, were introduced in the late 1970s and usually consist of polypropylene or glass. The sorbent bed is contained between two frits usually made from polyethylene or PTFE. Analysts can choose between a great variety of cartridge sizes and shapes, some of which have been specially designed to meet the requirements of automated SPE. The cartridge design has certain disadvantages, including the occurrence of channelling that negatively affects repeatability, and the small cross-sectional area. The latter limits the tolerance to blockage by suspended particles, thus leading to longer extraction times and low sampleprocessing rates, especially when dealing with large sample volumes, as in the case of water analysis. The SPE disk format was introduced in the early 1990s as an alternative to particle-filled cartridges. SPE disks (also called SPE membranes) do not contain the sorbent particles loosely packed, as in traditional SPE columns, but incorporated onto a support membrane that consist of porous PTFE or glass fibres, the latter being more rigid. The SPE particles used in PTFE membrane disks are smaller than those used in traditional SPE columns (e.g., 8 m versus typically 50 Am) and make ca. 90% of the total weight of the membranes. A great variety of sorbent types have already been embedded on SPE disk membranes, including various types of silicas (e.g., C18, C8, SCX, SAX), PS-DVB, modified PS-DVB (e.g., with cation and anion exchange functionalities) and ISs. The millimetre-thin disks are commercialized in three main sizes (2.8, 4 and 9 mm) and are placed in special holders to perform SPE by letting the liquid samples flow through. Green et al. presented an alternative arrangement for achieving trace enrichment of analytes from water samples by directly submerging C18 disks into the water, which was stirred with a stir bar [220]. SPE disk membranes are characterized by a uniform packing density and a large diameter compared with the thickness, which allows high and steady flow rates and faster throughput of large volume samples. Compared with loose-particle filled cartridges, the occurrence of channelling that causes breakthrough losses is significantly reduced and more reproducible results are reportedly achieved. Disks are also prone to clogging caused by particles in the sample, which is effectively prevented when a prefilter is used. One of the drawbacks of using disks instead of cartridges is their
179
M. Anastassiades and E. Scherbaum limited capacity and the smaller breakthrough volumes. When dealing with analytes that show weak retention, the use of two or more disks in the same device helps to increase retention. On the other hand, the lower retention power of disks compared with packed beds results in very small preconditioning and elution volumes and thus less need for post-elution concentration steps. SPE disks have lately also been incorporated into various other formats such as cartridges (cartridge disks), 96-well plates and pipette tips (see below). The call for lower solvent consumption and the higher sensitivity of analytical instruments have initiated a trend for miniaturization of SPE applications, both in the packed column and the disk format. The use of lower solvent volumes furthermore reduces the amount of solvent that has to be evaporated, thus speeding up the whole procedure. A survey by Majors [221] has shown a trend away from 500 mg and towards 100 mg packed beds in SPE cartridges. Fritz et al. [222] have employed 0.7 mm disks impregnated with polymeric sorbent particles that they incorporated into a syringe needle, achieving comparable results to conventional 4 mm disks. Recently, Saito and Jinno [223] have introduced a novel miniaturised adsorptive extraction device for dynamic extractions. Numerous thin fibres consisting of"Zylon", heterocyclic polymers packed into PEEK tubes, are used as adsorbents. The extraction takes place by passing the sample through the device [223]. With miniaturisation, automation and high-throughput sampling in mind, 96-well plates were introduced in the mid-1990s. The 128 x 86 mm-sized plates have been designed to fit on automated plate-handling systems and are equipped with 96 miniaturised devices filled either with sorbent particles (10-100 mg) or with appropriately sized SPE disks. Early 96-well platehandling systems were based on manual vacuum manifolds; however, newer, fully automated systems employ positive pressure. Elutions are performed with as little as 100-200 ul solvent. Lately, even 192-and 384-well plates have become available, which allow even higher sample throughput. The well plate format has enjoyed widespread application and rapid acceptance in laboratories working in the bioanalytical and pharmaceutical fields, where it is used for rapid sample preparation, in clinical studies and combinatorial drug synthesis. So-called modular devices (e.g., Versa-Plate) allow individual equipping of the plates with different sorbents, which can be very useful in automating method development. The 96-well plate technology has been reviewed by Wells [2241. SPE has recently been commercialised in disposablepipette tips that allow convenient performance of miniaturised applications. There are numerous manufacturers and designs of SPE pipette tips. Some contain loose sorbent 180
Sample handling and clean-up procedures II-new developments particles filled between two frits inside the pipette tips. Here, the sample is drawn and mixed with the stationary phase and then dispensed again. In other designs, the sorbent particles (normal or reversed phase) are impregnated onto the interior walls of the pipette tips in order to minimise plugging. 4.9.1.7 Automation and hyphenation The amenability to automation (or semi-automation) is one of the advantages of SPE and numerous efforts have been undertaken in this direction in the last three decades. Automation has been widely applied in SPE applications dealing with extraction/pre-concentration (mostly in water analysis) but less often for clean-up purposes [225]. Today, most, if not all, laboratories that use SPE utilise some form of semi-automation but still few utilise computercontrolled robot arms (workstations) to fully automate some or all of the steps. For many years, SPE has been mainly performed using manual vacuum manifolds that allowed single and multiple sample processing employing vacuum. However, these manual vacuum stations have some disadvantages: (1) they require attention by the personnel, (2) the flow rate is difficult to adjust, which may result in poor reproducibility, (3) the sorbent may dry out after conditioning, and (4) clogging may occur when dealing with certain sample types. Almost all fully automated modern workstations apply positive pressure using high-precision pumps, which eliminates a lot of the abovementioned disadvantages. SPE automation allows unattended operation, helps reduce the amount of monotonous repetitive work done by laboratory staff, helps increase sample throughput, provides better repeatability, facilitates method development and consequently helps to better exploit the potentials of SPE. A review on automation of SPE, which also focuses on online hyphenation, has been published by Rossi et al. [226]. With early automated SPE systems, individual samples were processed in series with the next sample starting after the preceding one had been completed. Contemporary serial processing equipment is able to extract 20-50 samples per hour. As regards speed, such systems are comparable or even slower than manual systems that allow extraction in batches of, for example, 12 samples using vacuum manifolds. Nevertheless, time savings still result from the ability to operate continuously during non-working hours as well. It should be kept in mind, however, that when analyte stability is an issue, sequential processing may be a problem. Starting in the 1990s, instruments were introduced that allowed automated parallel processing of samples. Such systems can process up to many hundreds of samples per hour. The configuration of SPE makes it easy to be hyphenated on-line to other analytical techniques, resulting in fully automated systems. Being highly 181
M. Anastassiades and E. Scherbaum
compatible with liquid chromatography, SPE is most often on-line-connected to HPLC [227,228]. SPE/LC is probably the most robust on-line arrangement used in residue analysis. Following the enrichment of analytes on the SPE cartridges, the extracts are subsequently transferred to the analytical column for further separation and detection. Modern instruments employ so-called "column switching arrangements", equipped with special valve systems to regulate the flow. It is important to consider that when the SPE sorbent used is more retentive than the analytical LC-phase, this may result in peak broadening due to the fact that the strong elution solvents required to displace the analytes from the SPE column will not allow proper analyte focusing and separation on the analytical column. An elegant approach to overcome this band-broadening problem involves the elution of the SPE pre-column in the backflush mode (in the reverse direction from extraction) and the dilution of the eluate with water before it reaches the analytical column [229]. 4.9.1.8 Applications Of all sample preparation techniques described here, SPE is the most widely used in pesticide residue analysis, with countless extraction and clean-up applications being published each year. Water analysis is probably the most prominent application field and SPE has been very well adapted to the handling of such samples. Very large volumes of filtered water can be passed through SPE cartridges/disks in a short time, providing simultaneous extraction and concentration as well as the possibility to conveniently store and transport sample extracts. For many years, multi-residue analyses of pesticides in water have been mainly performed using alkyl-silicas (mainly C18) [212,230,231] but this has changed with the introduction of polymeric high-capacity sorbents [212,231,232] and GCB [233]. The applications employing SPE are numerous and have been covered in a number of recent reviews [201-204,234]. Compared with water analysis, the use of SPE in food analysis is far less extensive. Some applications employing SPE for pesticide residue analysis in food are summarised in the following three tables: Table 4.9 focuses on the use of SPE for the enrichment of pesticides from liquid samples directly or after dilution and Table 4.10 shows some applications involving RP-SPE for the enrichment of pesticides from raw extracts of samples after dilution with water. A common problem associated with these two types of applications is that highly non-polar analytes (e.g., pyrethroids) may start to precipitate when the organic content becomes too low. On the other hand, even a small percentage of the organic solvent may drastically limit the extractability of polar analytes onto the SPE phase 235]. Similar observations have been
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Sample handling and clean-up procedures II-new developments noted in corresponding SPME and SBSE applications, as will be shown in the corresponding sections. In the case of oily matrices, analyte enrichment cannot be performed with reversed-phase sorbents; thus, NP sorbents are used to trap the analytes. For example, Barrek et al. [236] have isolated 22 pesticides from essential oils of citrus by dissolving them in pentane and pouring the extracts into a Florisil column. Various non-polar components such as terpenes were washed off with pentane, while the analytes were subsequently eluted with dichloromethan and analysed by GC/MS. Table 4.11 gives some examples of the use of SPE for the clean-up of extracts in traditional MRMs. The applications shown there employ SPE as a chemical filter to selectively remove certain co-extracted matrix components, allowing the analytes to pass through. 4.9.1.9 Discussion and perspectives Within the last 30 years, SPE, in its various forms, has steadily gained acceptance among analysts and has become one of the most frequently employed clean-up and trace-enrichment procedures in a variety of applications, including multi-residue analysis of pesticides. In water analysis, where SPE provides simultaneous extraction and concentration of multiple residues, the technique has meanwhile almost completely replaced the traditional extractions with organic solvents. Driven by the need for high-throughput analysis (mainly on behalf of the pharmaceutical industry), SPE is steadily improving in terms of sorbent chemistries, automation and applicability to high-throughput analysis. The importance of SPE is also reflected by the growing number of companies producing and marketing SPE products [221]. SPE offers many benefits, including high enrichment factors, ease of automation and hyphenation with final instrumental analysis, the ability to rapidly process multiple samples in parallel, reduced labour and also simplicity (although the devil lies in the detail). Compared with LLP procedures, SPE is characterised by an enormous reduction of solvent-related problems (purchase and disposal costs, human exposure, environmental pollution) and the elimination of emulsions. SPE further facilitates on-site sampling and eliminates the need for transporting large volumes of water back to the laboratory under refrigerated conditions. The great variety of sorbent types and retention mechanisms (RP, H-bond, Tr-Tr, ionic) give SPE a high potential for the selective enrichment of analytes and the removal of matrix interferences. This selectivity potential can be exploited to a fuller extent in single class or single analyte methods and less in multi-class-multi-residue applications, a limitation that is inherent to any 185
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Fig. 5.4. LVI-LC-MS-MS (PI mode; SRM) of (A) a potato extract spiked at the 5 g/kg level and (B) a non-spiked carrot extract. Peak assignment: (1) dimethoate; (2) metoxuron; (3) carbofuran; (4) atraton; (5) atrazine; (6) diuron; (7) linuron; (8) metolachlor, (9) diazinon and (10) internal standard 2H5 diazepam. Reproduced from Ref. [85].
obtained after LVI-LC-MS-MS of a spiked potato extract with 5 g/kg and a non-spiked carrot extract where 16 min was enough to identify all compounds. The main advantages of the technique were its simplicity, high precision and little organic solvent consumption. 5.4.2
Capillary electrophoresis coupled to LC
Capillary electrophoresis (CE) is becoming an attractive alternative to chromatographic techniques for the analysis of pesticides in fruits and vegetables. As indicated in a recent review, it offers high separation efficiency, fast analysis and easy operation at low costs [86]. The problems related
259
S. Lacorte and A.R. Ferndndez-Alba to inadequate limits of detection and a lack of selective detectors have been recently overcome by the development of off- and on-column trace enrichment schemes to improve method LODs. Off-column pre-concentration is achieved by liquid-liquid extraction (LLE) or SPE and on-column concentration using on-line SPE or stacking methods as a sample preparation method to be used in CE. LLE has been used to determine thiabendazole in fruits and vegetables using methylene chloride, and LODs of 400 ppb were obtained [87]. Malik et al. [88] extracted dimethyldithiocarbamate from grains using LLE with trichloromethane and LODs were of 700 ppb using a pre-concentration factor of 5. Several fungicides have been extracted from grain with water-acetone using SPE 0.5 mg C1 s and elution with methylene chloride and with a pre-concentration factor of 10; LODs were between 100 and 1000 /,g/l [89]. LODs of 0.05 ppb have been reported for the analysis of urea-derived herbicides in fruits and vegetables using also SPE with 0.5 mg C1 8 glass cartridge [90]. Thiabendazole and procymidone were analysed in fruits and vegetables using stacking methods with matrix removal and capillary zone electrophoresis [91]. LODs for the different compounds vary according to the detection system. However, injection precision performance is probably the most critical part in CE. In CE, injection volumes are typically of 5-50 nl and loop injectors for these tiny volumes are not available for current CE instruments [92]. Injections in CE are achieved by inserting the capillary into a sample solution vial and then pressurising the vial to force the sample solution into the capillary. The volume injected is directly related to the pressure difference and the time that the pressure has been applied. In any case, external factors such as siphoning, surface tension of the sample solution, viscosity and temperature affect the injection volume, which reduces detector linearity and leads to poor accuracy. In a standard solution, CE can give acceptable precision for 5-10 replicate injections [93] but it is impossible to maintain reproducibility in long sequence injections or the analysis of complex samples. To improve injection precision, the use of an internal standard has been suggested [92]. In CE, the internal standard should migrate reasonably near the solute peak of interest and it can also be used for quantification purposes. Coupling CE with MS is gaining interest due to the general trend to use MS for pesticide residue analysis in food and it is anticipated that it will be used as a routine tool in many food laboratories. In addition, as indicated by Rodriguez et al. [90], future trends will be for the adaptation of CE to microchips, which will allow extremely rapid separations that consume only picolitre-sample volumes and raise the possibility of integrating sample preparation and analysis in a single device.
260
Sample introduction techniques
5.4.3
SPME coupled to HPLC
A new SPME technique known as in-tube SPME has been developed for combination with LC or LC-MS using an open tubular fused-silica capillary column as SPME device instead of a SPME fibre and a desorption chamber utilised for solvent desorption prior to HPLC [94,95]. With in-tube SPME, organic compounds from the aqueous phase are extracted from the sample into a capillary column (with coatings similar to SPME fibres) and then analytes are desorbed by introducing a moving stream of mobile phase or static desorption solvent (instead of thermal desorption as was used in GC) depending on the chemistry of the compounds. The capillary column is placed between the injection loop and the injection needle of the HPLC autosampler. As in a normal injection, the injection syringe repeatedly draws and ejects sample from the vial, the analytes partition from the sample matrix to the stationary phase. Afterwards, extracted analytes are desorbed from the capillary coating by the mobile phase. The desorbed analytes are transported to the HPLC column for separation and posterior detection using any detection system (UV, DAD, MS). In-tube SPME coupled to LC has been applied to the determination of pesticides in water samples but sensitivity was limited by the UV detector and the commercial capillary used for extraction [96,97]. Although the applications of in-tube SPME for pesticide analysis in food are very rare, Wu et al. [97] applied it to determine polar pesticides (phenyl urea and carbamates) in water and wine samples and demonstrated that the extraction efficiency and method sensitivity can be increased by combining a polypyrrole-coated capillary and the use of LC-ESI-MS detection. Limits of detection were in the range of 0.01-1.2 ng/ml and a linearity in the range of 0.5-200 ng/ml. In-tube SPME can be automated and can continuously perform extraction, desorption and injection using a standard autosampler. Overall, shorter analysis times are achieved and the method provides better accuracy and precision.
5.4.4
On-line solid-phase extraction coupled to LC
As indicated in a previous section, there is a high tendency to use hyphenated techniques for the automated analysis of pesticides in food. As with on-line SPE-GC, the procedure is based on the use of an adsorbent material placed in a six-port valve. Samples (e.g., food extract reconstituted in water) are pumped through the pre-column, which can retain the pesticides from 261
S. Lacorte and A.R. Fernandez-Alba the aqueous solution. After percolation, the pre-column is rinsed, typically with water, and afterwards the position of the six-port valve is changed so that pesticides are selectively eluted with the HPLC mobile phase to the detector. In this case, elimination of water through the use of a retention gap is not necessary. In general, LODs at levels of ng/l and better reproducibility values can be obtained by using an on-line approach because the entire sample is transferred to the analytical column and losses during sample manipulation are minimised. At the same time, on-line methodologies are more sensitive since it is possible to analyse pesticides at a level of ng/l with only 100 ml of sample. The technique is especially recommended for the analysis of polar pesticides. Physical parameters of the sorbent material, such as pore diameter, particle size and its distribution, amount and type of sorbent, solvents used for extraction, washing and elution, volume of aqueous sample preconcentrated, etc., determine the extraction efficiency, which will vary depending on the pesticides. Breakthrough volumes according to the capacity and type of cartridge and chemistry of the compound should be calculated to avoid low recoveries. Cartridges are available from 30 mg to 2 g and packing materials are commonly C18, C8, polymeric or immunosorbent, and each material will have a different affinity for the problem compound. However, in order to achieve optimal performance with on-line SPE, the sorbent of the pre-column should be as close as possible to the analytical column packing in terms of type of packing, particle size, etc. Band broadening can be minimised by using a suitable gradient, which causes peak compression on the top of the analytical column. The size of the pre-column is also of importance because the elution profile of the analytes should be as narrow as possible, especially at the beginning of the separation where the high water content tends to cause peak distortion. For a classical analytical column of 15 cm x 0.46 cm I.D., common sizes are 2 mm long and 2-3 mm internal diameter packed with 10-60 /im sorbent material, which efficiently traps the analytes. SPE coupled on-line with LC has been successfully applied to the analysis of pesticides from food matrices. The SPE sorbent in this case basically acts as a clean-up step, which otherwise has to be performed in many cases on adsorption columns [98] or using disposable SPE cartridges [99]. De Kok and Hiemstra optimised an SPE clean-up method coupled on-line with LC with fluorescent detection for the detection of N-methylcarbamate pesticides in fruits and vegetables [99]. The automated clean-up step was performed on an ASPEC (Gilson, France) apparatus, which executes complete SPE clean-up automatically, followed by on-line injection of 100 l cleaned-up extract into 262
Sample introduction techniques the LC system. The limits of detection obtained were in the 5-50 g/kg range for 13 carbamates and 12 metabolites on 12 different food products (see Table 5.3). The system was validated and found suitable for the routine analysis of pesticide residues. Recently, Riediker et al. developed a method for the determination of chlormequat and mepiquat in pear, tomato and wheat using on-line SPE with the Prospek (Spark Holland, The Netherlands) coupled to LC-ESP-MS-MS [100]. The sample preparation consisted of extracting 10 g of sample with methanol and water (1:1) and, after the supernatant was filtered through 0.2 /im, 30 ldof the extract was transferred to the SPE cartridge. A strong cation-exchange resin was used and the whole procedure was controlled by the use of deuterated internal standards. The method was fully automated and enabled the quantitative and confirmatory determination of two quats in fruits and vegetables in routine quality control operations. Although one of the limitations of the system is the potential overload of the SPE cartridge when injecting highly concentrated extracts, the method is very versatile and can be adapted to different pesticide concentration values. With on-line SPE-LC, it is recommended to use MS as the detection system in order to avoid sample interferences due to carbohydrates, proteins, etc., which are pre-concentrated along with target analytes. As a precaution, it should be mentioned that on-line pre-columns can be easily clogged if the sample contains small food pieces. Therefore, the main advantages of on-line SPE-LC-MS can be summarised as: (i) no need to evapourate the final extract, therefore losses due to recomposition of the extract are avoided; (ii) elimination of the sample matrix by choosing an appropriate SPE sorbent and cleaning/elution solvent composition, which is especially relevant in food analysis where the matrix can produce interfering ions that produce a distorted spectra, which could not be used for analyte confirmation; (iii) inhibition of ion suppression due to the fact that a cleaner chromatogram is obtained; (iv) lower LODs obtained even when analysing small amounts of sample since all the sample is transferred to the HPLC system; and (v) capacity to trap very volatile, water-soluble pesticides. Even though in routine food analysis there is a tendency to replace off-line methods with automated methods, on-line SPE does not avoid sample extraction as it does for water analysis. Although at present there are still not many applications dealing with on-line SPE -LC -MS, this is more related to the fact that GC-MS remains the preferred approach for the survey of pesticides in food. However, the benefits are clear, as indicated by Torres et al. in a complete review on determination of pesticide residues in fruit and vegetables [4].
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S. Lacorte and A.R. Ferndndez-Alba 5.5
CONCLUSIONS
Although pesticide residue analysis is well established, there is still some need for fast, cost-effective and automated methods to satisfy the routine export/import survey of a large number of pesticides in fruit and vegetables. Modern trends are directed to minimum sample preparation and implementing high-throughput automated injection using equipment, which high sensitivity to be achieved as well as sample throughput and the possibility of analyte confirmation. Mass spectrometric detection fulfills such requirements provided the injection technique is automated for an upgrade method performance. By using GC techniques, pesticide residues in foods can be analysed with split/splitless injection on column injection or PTV. The selection of one type or another depends basically on the chemistry of the target analytes. While the former is especially suitable for volatile compounds, on-column is preferably employed for thermolabile pesticides. On the other hand, PTV permits LVI, making the technique especially suitable for achieving low method detection limits. As a novel sample introduction technique, coupling SPME with GC has proven to be very suitable for the extraction and quantification of pesticides from different types of fruit and vegetables and results are very promising as regards recoveries, precision, LODs, sample throughput and costs. SPME can also be coupled to LC, the main advantage being the possibility to determine polar, thermolabile and non-volatile pesticides. The applicability of this technique will probably replace the typical protocol of sample preparation, extraction and analysis by the traditional 20 /l loop. However, it is envisaged that in the near future online SPE coupled to LC-MS will also be applied to analysing pesticides in food with minimal sample preparation and automated clean-up, thus achieving high sensitivity. Most of the above-mentioned injection techniques are already widely used for pesticide analysis, some are under development and their applicability is to be demonstrated and others, especially hyphenated techniques, have a high potential in pesticide quality control laboratories due to the reduction of costs and analysis time. All the techniques described are meant to facilitate the analysis of an increasing number of pesticides in fruits and vegetables.
Acknowledgements The authors thank Ana Aguera for providing some figures and Roser Chaler for her useful comments on the manuscript. 264
Sample introduction techniques REFERENCES 1 2 3 4 5 6 7 8 9 10 11 12 13
14 15 16 17 18 19 20 21 22 23 24 25 26
W. Specht, S. Pelz and W. Gilsbach, Fresenius J. Anal. Chem., 353 (1995) 183. J. Fillion, R. Hindle, M. Lacroix and J. Selwyn, J. Assoc. Off. Anal. Chem. Int., 78 (1995) 1252. N. Motohashi, H. Nagashima, C. Pdrkanyi, B. Subrahmanyam and G. Zhang, J. Chromatogr.A, 754 (1996) 333. C.M. Torres, Y. Pic6 and J. Maiies, J. Chromatogr.A, 754 (1996) 301. J.L. Tadeo, C. Sanchez-Brunette, R.A. Perez and M.D. Ferndndez, J. Chromatogr. A, 882 (2000) 175. S.J. Lehotay and J. Hajslovd, TRAC, 21(9/10) (2002) 686. D.R. Erney, T. Pawlowski and C.F. Poole, J. High Resolut. Chromatogr., 20 (1997) 375. J.V. Hinshaw, LC-GC Europe, March (2003). K. Grob, Th. Laubli and B. Brechbuihler, J. High Resolut. Chromatogr., 11 (1988) 462. R.L. Grob, Modern Practice of Gas Chromatography.Wiley, New York, 1995. J. Staniewski and J.A. Rijs, J. High Resolut. Chromatogr., 16 (1993) 182. M. Abdel-Rehim, K.A. Svensson, Y. Askemark and K.J. Pettersson, J. Chromatogr.B, 775(1/2) (2001) 253. M. Mifiones Vazquez, M.E. Vdzquez Blanco, S. Muniategui Lorenzo, P. L6pez Mahia, E. Fernandez Ferndndez and D. Prada Rodriguez, J. Chromatogr.A, 919 (2001) 363. A. Aguera, M. Contreras and A.R. Fernindez-Alba, J. Chromatogr.A, 655 (1993) 293. A.R. Ferndndez-Alba, A. Valverde, A. Aguera and M. Contreras, J. Chromatogr. A, 686 (1994) 263. H.J. Stan and H.M. Muller, J. High Resolut. Chromatogr., 11 (1988) 1405. H.M. Miiller and H.J. Stan, J. High Resolut. Chromatogr., 13 (1990) 759. P.-L. Wylie, R.J. Phillips, K.J. Klein, M.Q. Thompson and B.W. Hermann, J. High Resolut. Chromatogr., 14 (1991) 649. P.L. Wylie, K.J. Klein, M.Q. Thompson and B.W. Hermann, J. High Resolut. Chromatogr., 15 (1992) 763. P.L. Wylie and K. Uchiyama, J. Assoc. Off Anal. Chem., 79 (1996) 57. M. Godula, J. Hajslova and K. Alterova, J. High Resolut. Chromatogr., 22(7) (1999) 395. J. Hajslovd, K. Holadovd, V. Kocourek, J. Poustka, M. Godula, P. Cuhra and M. Kempny, J. Chromatogr.A, 800 (1998) 283. J.C. Chuang, K. Hart, J.S. Chang, L.E. Boman, J.M. van Emon and A. Reed, Anal. Chim. Acta, 444 (2001) 87. E.M. Kristenson, E.G.J. Haverkate, C.J. Slooten, L. Ramos, R.J.J. Vreuls and U.A.Th. Brinkman, J. Chromatogr.A., 917 (2001) 277. F.J. Egea, M.E. Hernandez Torres, E. Almansa L6pez, L. Cuadros-Rodriguez and J.L. Martinez-Vidal, J. Chromatogr.A, 9666 (2002) 155. A. Aguera, L. Piedra, M.D. Hernando, A.R. Fernindez-Alba and M. Contreras, Analyst, 125 (2000) 1397.
265
S. Lacorte and A.R. Ferndndez-Alba 27 28 29 30 31 32 33 34 35 36 37 38 39 40
41
42 43 44 45 46 47 48 49 50 51 52 53 54 55 56
266
J. Beltran, F.J. Lopez, M. Focarda and F. Hernandez, Anal. Chim. Acta, 356 (1997) 125. J. Beltran, F.J. Lopez, M. Focarda and F. Hernandez, Chromatographia,44(5/6) (1997) 274. G. Nissner, W. Buchberger and R. Eckerstorfer, J. Chromatogr.A, 846 (1999) 342. W. Vogt, K. Jacob and H.W. Obwexer, J. Chromatogr., 174 (1979) 437. W. Vogt, K. Jacob, A.B. Ohnesorge and H.W. Obwexer, J. Chromatogr., 186 (1979) 197. Z.E. Penton, J. Assoc. Off: Anal. Chem., 74 (1991) 872. G. Schomburg, H. Husmann and F. Schulz, J. Chromatogr., 279 (1983) 689. F. Poy, S. Visan and F. Terrosi, J. Chromatogr., 217 (1981) 81. R.S. Sheridan and J.R. Meola, J. Assoc. Off. Anal. Chem. Int., 82 (1999) 982. W. Engewald, J. Teske and J. Efer, J. Chromatogr.A, 856 (1999) 259. H.G.J. Mol, M. Althuizen, H.-G. Janssen and C.A. Cramers, J. High. Resolut. Chromatogr., 119 (1996) 69. J. Villen, F.J. Sefiorans, M. Herraiz andJ. Tabera,J. Chromatogr.Sci., 36(1998) 535. F.J. Sefiorans, J. Tabera, J. Vill6n, M. Herraiz and G. Reglero, J. Chromatogr., 648 (1993) 407. E. Concha-Grafia, M.I. Turnes-Carou, S. Muniategui-Lorenzo, P. L6pez-Mahia, E. Ferndndez-Ferndndez and D. Prada-Rodriguez, J. Chromatogr.A, 958 (2002) 17. M. Mifiones-Vazquez, M.E. Vdzquez-Blanco, S. Muniategui-Lorenzo, P. L6pezMahia, E. Fernandez-Fernandez and D. Prada-Rodriguez, J. Chromatogr.A, 919 (2001) 363. H.J. Stan and M. Linkerhagner, J. Chromatogr. A, 727(2) (1996) 275. M. Hada, M. Takino, T. Tamagami, S. Daishima and K. Yamagushi, J. Chromatogr.A, 874 (2000) 81. P.L. Wylie, application note, Agilent Technologies, USA, September 1997. H.M. Miller and H.J. Stan, J. High Resolut. Chromatogr., 13 (1990) 697. M. Godula, J. Hajslova, K. Alterova and J. Krivankova, J. Sep. Sci., 24(5) (2001) 355. J. Zrostlfkov6, J. Hajslova, M. Godula and K. Mastovska, J. Chromatogr.A, 937 (2001) 73. S. Schachterle and C. Feigel, J. Chromatogr. A, 754 (1996) 411. J.L. Martinez Vidal, F.J. Arrebola and M. Mateu-Sanchez, J. Chromatogr.A, 959 (2002) 203. J. Dalluige, M. van Rijn, J. Beens, R.J.J. Vreuls and U.A.Th. Brinkman, J. Chromatogr. A, 965 (2002) 207. K. Mastovska, S.J. Lehotay and J. Hajslova, J. Chromatogr.A, 926 (2001) 291. K. Grob and M. Bronz, J. Microcol. Sep., 7(4) (1995) 421. U.A.Th. Brinkman, J. Slobodnik and J.J. Vreuls, Trends Anal. Chem., 13 (1994) 373. S. Lacorte and D. Barcel6, Anal. Chem., 68(15) (1996) 2464. A.J.H. Louter, C.A. van Beekvelt, P. Cid Montanes, J. Slobodnik, J.J. Vreuls and U.A.Th. Brinkman, J. Chromatogr.A, 725(1) (1996) 67. E.R. Brouer, S. Kofman and U.A.Th. Brinkman, J. Chromatogr. A, 703(1/2) (1995) 167.
Sample introduction techniques 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90
A. Column, S. CArdenas, M. Gallego and M. Valcarcel, J. Chromatogr. A, 882 (2000) 193. T. Hyotylainen, K. Jauho and M.L. Riekkola, J. Chromatogr.A, 813 (1998) 113. K. Grob and I. Kalin, J. Agric. Food Chem., 39 (1991) 1950. M. De Paoli, M.T. Barbina, R. Mondini, A. Pezzoni, A. Valentino and K. Grob, J. Chromatogr., 626 (1992) 145. B. Jongenotter and H.G. Janssen, LC-GC Europe, June (2002). C.L. Arthur and J. Pawliszyn, Anal Chem., 62 (1990) 2145. Z. Zhang, M.J. Yang and J. Pawliszyn, Anal. Chem, 66 (1994) 844A. H. Kataoka, H.L. Lord and J. Pawliszyn, J. Chromatogr.A, 880 (2000) 36. J. Beltran, F.J. L6pez and F. Fernandez, J. Chromatogr.A, 885 (2002) 389. A.A. Boyd-Boland and J.B. Pawliszyn, J. Chromatogr. A, 701 (1995) 163. A.L. Simplicio and L.V. Boas, J. Chromatogr. A, 833 (1999) 35. J.J. Jim6nez, J.L. Bernal, M.J. del Nozal, M.T. Martin and A.L. Mayorga, J. Chromatogr.A, 828 (1998) 269. C.G. Zambonin, A. Cilenti and F. Palmisano, J. Chromatogr.A, 967 (2002) 255. A. Naval6n, A. Prieto, L. Araujo and J.L. Vilchez, J. Chromatogr. A, 975 (2002) 355. A.A. Boyd-Boland, S. Magdic and J. Pawliszyn, Analyst, 121 (1996) 929. R. Batlle, C. Sanchez and C. Nerin, Anal. Chem., 71 (1999) 2417. Y. Pic6, G. Font, J.C. Molt6 and J. Mafies, J. Chromatogr.A, 882 (2000) 153. R. Carabias Martinez, E. Rodriguez Gonzalo, M.J. Amigo Moran and J. Hernandez Mendez, J. Chromatogr., 607 (1992) 37. A.R. Fernzindez-Alba, A. Valverde, A. Agiiera, M. Contreras and S. Chiron, J. Chromatogr.A, 721 (1996) 97. C. Blasco, M. Ferndndez, Y. Pic6, G. Font and J. Mafies, Anal. Chim. Acta, 461 (2002) 109. J. Hau, S. Riediker, N. Varga and R. Stadler, J. Chromatogr.A, 878 (2000) 77. E. Watanabe, Y. Yoshimura, Y. Yuasa and H. Nakazawa, Anal. Chim. Acta, 433 (2001) 199. S. Ben Rejeb, C. Cleroux, J.F. Lawrence, P.-Y. Geay, S. Wu and S. Stavinski, Anal. Chim. Acta, 432 (2001) 193. E. Lacassie, M.F. Dreyfuss, J.L. Daguet, M. Vignaud, P. Marquet and G. Lachatre, J. Chromatogr. A, 830 (1999) 135. M.C. Peeters, I. Defloor, J. Coosemans, J.A. Delacour, L. Ooms, R. Deliver and D. De Vos, J. Chromatogr. A, 920 (2001) 255. M.J. Taylor, K. Hunter, K.B. Hunter, D. Lindsay and S. Le Bouhellec, J. Chromatogr. A, 982 (2002) 225. M. Hiemstra and A. de Kok, J. Chromatogr. A, 972 (2002) 231. A.C. Hogenboom, M.P. Hofman, S.J. Kok, W.M.A. Niessen and U.A.Th. Brinkman, J. Chromatogr.A, 892 (2000) 379. Y. Pic6, R. Rodriguez and J. Maiies, Trends Anal. Chem., 22(3) (2003) 133. D.T. Eash and R.J. Bushway, J. Liq. Chromatogr.Relat. Technol., 23 (2000) 261. R. Rodriguez, Y. Pic6, G. Font and J. Mafies, J. Chromatogr A, 924 (2001) 387. A.K. Malik, B.S. Seidel and W. Faubel, J. Chromatogr.A, 857 (1999) 365. R. Rodriguez, Y. Pic6, G. Font and J. Mares, Electrophoresis, 22 (2001) 2010. R. Rodriguez, Y. Pic6, G. Font and J. Mafies, J. Chromatogr.A, 949 (2002) 359.
267
S. Lacorte and A.R. Fernandez-Alba 91 92 93 94 95 96 97 98 99 100
268
K.D. Altria, LC-GC Europe, September (2002). B.R. Thomas, X.G. Fang, X. Chen, R.J. Tyrrell and S. Ghodbane, J. Chromatogr., 657 (1994) 383-394. R. Eisert and J. Pawliszyn, Anal. Chem., 69 (1997) 3140. H. Kataoka, H.L. Lord and J. Pawliszyn, Anal. Chem., 71 (1999) 4237. Y. Gou, R. Eisert and J. Pawliszyn, J. Chromatogr.A, 873 (2000) 137. Y. Gou, C. Tragas, K.L. Lord and J. Pawliszyn, J. Microcol. Sep., 12 (2000) 125. J. Wu, C. Tragas, H. Lord and J. Pawliszyn, J. Chromatogr.A, 976 (2002) 357. T. Cairns, M.A. Luke, K.S. Chiu, D. Navarro and E. Siegmund, Rapid Commun. Mass Spectrom., 7 (1993) 1070. De Kok, M., Hiemstra, J. Assoc. Off. Anal. Chem. Int., 75(6) (1992) 1063. S. Riediker, H. Obrist, N. Varga and R.H. Stadler, J. Chromatogr. A, 966 (2002) 15.
Chapter 6
GC-MS. I: Basic principles and technical aspects of GC-MS for pesticide residue analysis Hans-Jiirgen Stan
6.1
INTRODUCTION AND SCOPE
Mass spectrometry has gained a position of outstanding importance in many areas of organic chemical analysis. The technique can be combined on-line with the most important chromatographic separation techniques applied in trace analysis of biological, environmental and food samples: capillary gas chromatography and high-performance liquid chromatography. Both these "hyphenated techniques", GC-MS and LC-MS, are nowadays indispensable for sensitive positive structural identification of pesticides and other pollutants in our environment. These techniques are extremely valuable for the development of analytical methods to meet the low maximum tolerance values as set by the European Union and other legislative bodies for pesticides in foodstuffs. Therefore, a brief review of the principles of mass spectrometry is presented to survey the basics and to emphasize what makes this technique the unrivaled detection method in pesticide residue analysis. To date, virtually no analytical result can be considered as reliable if it does not include a mass spectrometric confirmation!
6.2
THE MASS SPECTRUM
The mass spectrum is a plot of the intensity as a function of the mass-tocharge ratio (Fig. 6.1). The peak with the highest intensity in the spectrum is called the base peak. Generally, the spectrum is normalised to the intensity of the base peak, resulting in relative intensities. Comprehensive Analytical Chemistry XLIII Ferndndez-Alba (Ed.) © 2005 Elsevier B.V. All rights reserved
269
H.-J. Stan Basepeak Ah llnrInrn IUUl -- I I.G
1 1 I
175
100 90-
80 Fragments
70 60 50
Fragme lts
75
40
7
99
30
127
20 101 I m/z--> u
....
8,t100I X1 80 n
..
120
Isotopic Peak
140
160
,...
180
.. I I.
200
.
302 I
220
240
260
280
300
Fig. 6.1. The mass spectrum.
When a molecule is ionised, a molecular ion M +' is produced and this may contain sufficient internal energy to fragment by ejection of a neutral particle N with the formation of a fragment ion A' + or A+ . The original analyte molecule gives a radical-cation as the molecular ion, and the fragment ion may be a cation or a radical-ion. The ejected neutral particle N may be a radical or a neutral molecule: M + e
M'+
-A
M'+
-A'
+
+ N'
or M + e
+N +
If the fragment ion has sufficient internal energy, then further fragmentation may occur with the formation of a whole series of fragment ions: M'+-N -
A + -NA -
B
-NB -
C+-
or M '+ -N - Z '+ -N
z
- Y'-Ny - X + ..
Such a series of decompositions when elucidated from a mass spectrum is called a fragmentation pathway. As shown, the molecular ion M' + may decompose by more than one pathway. The various fragmentation pathways together compose a fragmentation pattern characteristic of the compound under investigation.
270
GC-MS. I: Basic principles and technical aspects of GC-MS Ions
10
20
30
40
50
60
70
80
90
Electron Energy (eV)
Fig. 6.2. Total ionisation current as function of ionisation energy.
The extent to which fragmentation takes place along the individual pathways is determined by the amount of internal energy originally given to the molecular ion M' and its structure. Hence, the mass spectrum is not simply a fragmentation pattern but its appearance depends upon the energy of the ionising electrons and also upon the temperature at which ionisation occurs.
Ion formation as a function of the energy of ionising electrons in the electron impact process is illustrated in Fig. 6.2. The electrons are provided by a heated filament in the evacuated ion source, accelerated through a potential and directed across the chamber where they may hit the analyte molecules. The potential is continuously variable between 0 and over 100 eV. Molecular ions begin to appear around 10 eV (ionisation energy or appearance potential) but at low intensities. Between 10 and 15 eV, fragment ions also begin to appear. Both types of ions increase in abundance following individual abundance curves. Standard mass spectra are obtained at 70 eV because maximum ion yield (total ion current) is observed at this value and mass spectra were found to be reproducible and characteristic of the molecule ionised almost independent of the type and make of instrument. 6.3
STRUCTURAL INFORMATION
Although the structural identification of a pesticide in a pesticide residue analysis is usually performed by means of a reference spectrum of a standard
271
H.-J. Stan compound, a basic understanding of the interpretation of mass spectral data is certainly necessary to produce sound results. This holds true in particular if new compounds or derivatives with unknown mass spectra are to be inserted in the user's own mass spectral library. 6.3.1
The molecular ion
In a mass spectrum, several major kinds of general structural information are available. The molecular weight is probably the most valuable piece of information a mass spectrum can give. The molecular weight is calculated from the integer masses of the most abundant isotopes of the atoms present in the molecule and thus in the molecular ion. The molecular ion, also called the parent ion, is the peak that usually corresponds with the highest mass isotope cluster in the spectrum. However, identifying that peak with certainty can be rather difficult in some cases. In such cases, soft ionisation methods can be applied to produce ions indicative of the molecular weight. In pesticide residue analysis, chemical ionisation is the soft ionisation method mostly used for the production of "quasi-molecular" ions as the protonated molecule [M + H]+ is frequently referred to. In an electron ionisation (EI) mass spectrum, the fragment ions should be consistent with the molecular ion; peaks like [M - 1] + , M - 15] + , [M - 18] + and [M - 20] + confirm the assignment of the molecular ion because they represent the losses of H', CH', H 2 0 and HF, respectively, from the parent ion. Such "small-neutral loss" peaks are of major significance in deducing the molecular structure. Lists of common, small, neutral fragments lost in the formation spectral peaks are given in textbooks on mass spectrometry [1,2]. On the other hand, losses of 3-14 and 21-25 amu generally are not consistent with fragments formed from the parent ion and indicate an incorrect assignment or the presence of impurities. With mass spectra obtained with GC-MS or LC-MS analysis, the recognition of ions originating from impurities (background or not resolved chromatographic peaks) is generally facilitated by observing the relative ion abundances in the chromatographic peak. This method is also used in an automated form as background subtraction. As well as the molecular ion, two other types of peaks are observed in the mass spectrum: fragment and isotopic peaks. 6.3.2
Isotopic peaks
The isotopic peaks are the result of natural isotope abundances of the individual elements, which can be highly indicative. For instance, natural 272
GC-MS. I: Basic principles and technical aspects of GC-MS TABLE 6.1 Natural isotopic abundances of common elements Element
Mass
%
Mass
%
H C N 0 F Si P S Cl Br I
1 12 14 16 19 28 31 32 35 79 127
100 100 100 100 100 100 100 100 100 100 100
2 13 15 17
0.015 1.1 0.37 0.04
18
0.20
29
5.1
30
3.4
33
0.79
34 37 81
4.4 32.0 97.3
Mass
%
Type A A+ 1 A+ 1 A+ 2 A A+ 2 A A+ 2 A+2 A+ 2 A
chlorine exists as 75% 3 5 Cl-isotopes and 25% 3 7 C1-isotopes and consequently each parent or fragment ion containing chlorine can be easily identified by its typical chlorine isotopic cluster. The abundances of isotopic peaks at unit resolution from elements occurring in pesticides are given in Table 6.1. There are mono-isotopic elements such as fluorine, iodine, phosphorus and also hydrogen, which are referred to as "A"-elements and others with typical additional isotopic peaks in the spectrum such as chlorine, bromine and sulphur that arise at two mass units higher and therefore are designated as "A + 2" elements. Molecular and fragment ions containing more than one chlorine or bromine atom therefore give rise to very characteristic patterns, as shown in Fig. 6.3. The isotope patterns to be expected from any combination of elements can readily be calculated and provide a useful test of ion composition. Furthermore, in compounds containing C, H, O and the heteroatoms listed in Table 6.1, the molecular weight must be even. Thus, if a molecule contains one or an odd number of nitrogen atoms, the molecular weight will be odd. This generalisation applies to all stable even-electron molecules (the "nitrogen rule"). 6.3.3
Fragmentation reactions
Molecular ions are generated in the El ion source with a wide range of internal energies with a significant proportion being above the threshold for fragmentation. 273
H.-J. Stan I LU -
100 -
_
i.ILi LiL.
80 60 -
L
40 20 0 ClI
1I
C2
CI
CI
C155
C6 C
-
100 -
O
I
,11 I ,i .l , ,l. Br
Br 2
Br 3
Br 4
I_
.1
CIBr
CI 2Br
1zu 100806040200.
I LL ,
CI 3Br
1Ub.,
CIBr2
,
,
CI 2 Br2
,
CIBr2
LiI L ,
CIBr 3
I
CI2 Br3
Fig. 6.3. Isotopic clusters. Mass spectral reactions are unimolecular; the sample pressure in the El ion source is kept sufficiently low to avoid collision reactions. The mass spectrum reflects the results of a series of competing and consecutive reactions occurring in the ion source. The reactions are thought to be initiated at the favoured site for the unpaired electron and for the positive charge in the parent ion. The most favoured radical and charge site in the molecular ion is assumed to arise from loss of the molecule's electron of lowest energy. Favourability for ionisation generally is in the order of o- < IT < n-electrons from sigma bonds, double bonds (olefinic or phenyl) or non-bonding electron pairs, respectively.
274
GC-MS. I: Basic principles and technical aspects of GC-MS Sigma-bond dissociation is typical for alkane fragmentation. The electron lost in the ionisation comes from a saturated bond. The more abundant fragment will be the one better able to stabilise the positive charge. In unbranched alkanes, the sigma-bonds are nearly equivalent in bond strength. The resulting mass spectra can have many peaks of regularly varying abundances with only a small molecular ion, which can often not be identified. The alkane spectra are easily recognised by their typical ion series with mass differences of 14 (CH 2 ) and therefore were called "picket fence" spectra. They were observed in nearly all chromatograms from environmental samples. R-CH 2 -R' -· R' + +CH 2 -R'
R- CH 2 - R' - R- CH2 + +R' Reaction initiation at the radical site arises from its strong tendency for electron pairing. The electron is donated to form a new bond to an adjacent atom. This is accompanied by cleavage of another bond. This reaction is commonly called "a-cleavage". A well-known example is the allylic cleavages with the electron lost in the ionisation from an allylic double bond: R-CH 2 -CH'+-CH
2
- R' + CH2 =CH-CH+
Another characteristic example is the formation of the benzylium or tropylium ion from alkyl substituted aromatic compounds: H rr.-RR
_R
°
R
CH 2
+
H
H H
0-R~H H
H
Since ionisation by loss of an electron from a non-bonding electron of a heteroatom is favoured, fragments resulting from such cleavage reactions are abundant. The cleavage reaction is initiated by the positive charge which attracts an electron pair. The tendency for the formation of R + from R-Y parallels the inductive effect of Y. Therefore, it is called "inductive cleavage" with halogens > O, S > N. As well as simple bond cleavage reactions, rearrangement reactions are observed. In particular, hydrogen atom rearrangements initiated at a radical site are an important class of reactions. Such hydrogen rearrangements through six-membered ring intermediates are usually referred to as the "McLafferty rearrangement". For compounds containing an unsaturated 275
H.-J. Stan functionality such as the carbonyl group, the y-hydrogen atom is transferred by a sterically favourable transition state: H O
I C-H CH2
/R C
I
-
-R-CH=CH2
,CH2Z
2
H
/H 0+ -I CCH2
0+ -Z
CH
2
Summarising, the most important factor affecting the abundance of a product ion is its stability, which is caused by resonance stabilisation (allyl or benzyl cation) or electron sharing involving a non-bonding orbital of a heteroatom, such as in an acyl ion R- C'=O - R-C=O'+ . Another important driving force is the formation of small, stable, neutral products such as H 2 0, C 2H 4 , CO, CH 3OH, HCI and CO 2 with production of a more stabilised radical ion. The significance of small, neutral loss peaks for the identification of the molecular ion in a mass spectrum has already been emphasised [1,2]. 6.3.4
Interpretation
The principles reviewed are now illustrated with a few examples. Chlorinated pesticides are presented in Figs. 6.4-6.6 in order to demonstrate how to apply the basic knowledge to check the mass spectra and their assignment to a chemical structure for plausibility. Let us start with the methyl esters of 2,4-D and dichlorprop, two herbicides of very similar chemical structure; dichlorprop is derived from 2,4-D by simply substituting one hydrogen in the side chain by a methyl group. Both compounds exhibit abundant molecular ions with that of dichlorprop 14 amu higher than that of 2,4-D, as expected. The initially formed molecular ions are sufficiently stable, as with many aromatic compounds observed, to yield high abundances; they are the second largest peaks in the spectra. Both molecular ions exhibit even numbers and show the characteristic isotopic cluster that indicate compounds containing two chlorine atoms in their molecules, as can be drawn from Fig. 6.4. The fragments with the highest mass are [M - 35] + with 2,4-D and [M - 59]+; with dichlorprop representing the loss of chlorine from 2,4-D and a methoxycarbonyl from dichlorprop both easy to interpret, they confirm the molecular ions. No small fragment losses are observed. The base peak m/z 199 in 2,4-D exhibits the expected isotopic cluster of one chlorine confirming the formation of that fragment by loss of one chlorine: [M - 35] + . Note that the other fragments all contain two chlorine 276
GC-MS. I: Basic principles and technical aspects of GC-MS Ahbundnce.
90 80 70 60 50; 40 30 20 10 m/7_
n
199
CI
M.+
Cl2 Cl2
175
C2
73
ill 1 80
100
175
133145
II
II 120
234
CI2
11
140
161
;Ij
38
II~~~~~~~~~~~ 160
180
200
220
240
234
Fig. 6.4. Mass spectrum of the methyl ester of 2,4-D and the fragmentation pattern. atoms and therefore support the fragmentation pattern given in Fig. 6.4. This also holds true for the fragmentation pattern given for the mass spectrum of dichlorprop in Fig. 6.5. The base peak in this spectrum is m/z 162, which can only be explained by a hydrogen rearrangement. The formation of the peak may include a radical site rearrangement with transference of a hydrogen from the branched methyl group to the phenolic oxygen. Note the different fragmentation pattern in the two similar molecules; the dichlorophenolic ion m/z 161 is formed from both compounds with low abundances by inductive cleavage. The possibility of undergoing a rearrangement with hydrogen migration, however, makes the formation of the dichlorophenol ion
at m/z 162 so favourable that it constitutes the base peak in the mass spectrum. The small difference in the chemical structure between two closely related compounds leads to mass spectra of completely different appearance. Thus, these two "homologous" pesticides back up the statement that mass spectra are indicative of individual compounds and can reflect small changes in the chemical structures.
277
H.-J. Stan Abundance
162
Cl2
90 80 70 60 50 40 30 20 10 _/_
~59
Cl
1 60
133
100
189
248
191
250
120
FL
15
1 1, 1~~1 41II.
80
M° +
CI 2
109
n
CI2
140
160
.. h ...... 180
200
220
240
260
248 189-
145 0 H3 C-OCH 3
Cl Cl -co
133 -161 + H
Fig. 6.5. Mass spectrum of the methyl ester of dichlorprop and the fragmentation pattern.
The third example shown is the mass spectrum of folpet, a chlorinated fungicide with a chlorine substituted in a methylthio group (Fig. 6.6). The active compound contains the heteroatoms nitrogen and sulphur in addition to the three chlorines. With only one nitrogen in the molecule, the molecular ion has an odd number and is observed at a relative abundance of 30% due to its aromatic structure. The base peak ion is formed by a favourable loss of one single chlorine from the trichloromethylthio group by inductive cleavage, as expected. Only a small proportion in this reaction retains the positive charge at the trichloromethyl part (m/z 117). There is only one other chlorinecontaining fragment ion at m/z 232, which is formed by small, neutral loss of CO. Other fragments can be explained by successive decomposition of the thiophthalimide moiety, as partly indicated. Fragments retaining the aromatic acid structure are C 6 H 4 CO+ at m/z 104 and C6H4+ at m/z 76, as characteristic for a substituted benzene ring. The only fragment difficult to
278
GC-MS. I: Basic principles and technical aspects of GC-MS Abundance
26n
90 80 70 60 50 40 30 20 10 lII/--U ' U
CI2
M.+
C13
CI3
104 76
130 117
CI2 178
~ 11 80
100 120
-Co 232 -C-
X~
140
160
295
232
I II . . . . . .... . .... .. 180 200 220 240 260 280
300
295
260
-S--C
O
178
Cl
ICI
117
Fig. 6.6. Mass spectrum of folpet and fragmentation pattern.
interpret is that at m/z 130, which must be formed through a complex rearrangement from the phthalimide moiety. The interpretation seems to be plausible with the chemical structure because all other major peaks can be arranged in a consistent fragmentation pattern.
6.4
CHEMICAL IONISATION
It became clear in the description of the basics of mass spectrometry and the interpretation of EI mass spectra that with several compounds the structural information is limited. In particular, the molecular weight should be unequivocally determined. Chemical ionisation (CI) is the method of choice that can be easily applied using the mass spectrometer as a chromatographic detector. In LC-MS, CI is
279
H.-J. Stan the main ionisation technique (see chapter 7). CI is very useful in that most molecules that do not yield molecular ions by EI can produce ions with CI indicative of the molecular weight. Furthermore, CI conditions produce abundant thermal electrons that form highly efficient negative ions from molecules with high electron affinity by electron capture, a process familiar to the pesticide residue analyst from the electron capture detector. For CI, a reagent gas is introduced into the ion source at a concentration in large excess to that of the analytes (104:1). The reagent gas is usually ionised by electron bombardment as in EIl. The formation of primary ions is followed by ion molecule reactions between those primary ions and the gas neutrals, producing the chemical ionisation reagent ion or a variety of such reagent ions as well as the thermal electrons [3]. 6.4.1
Positive ions
Methane is employed for chemical ionisation as the reagent gas most frequently because almost all organic molecules are ionised. The reactive species are formed by the following reactions: CH 4 + e -- CH'+, CH+, CH", etc. CH'+ + CH 4 - CH+ + CH' CH+ + CH 4
-
C 2H+ + H 2
CH' + CH 4 - C2H+ + H 2 + H' C 2H+ + CH4 - C3 H + + H2 At pressures around 1 Torr, more than 90% of the ion population consists of the ions CH +, C 2H and C 3 H with m/z 17, 29 and 41, respectively. CH+ reacts exothermically with almost all organic molecules behaving as a Bronsted acid to yield a protonated molecular ion: M + CH+ - [M + H] + + CH 4 Other reactions that can be observed are M + CH+ -- [M - H] + + CH 4 + H2 M + C 2H M + C 3H
[M + C2 H5 ] +
- [M + C 3H 5] +
The latter two equations show bimolecular association reactions, which are generally classified as solvation processes in the gas phase. 280
GC-MS. I: Basic principles and technical aspects of GC-MS TABLE 6.2 Proton affinity of reactant gases Gas
Reactant ion
Proton affinity (kJ/mol)
CH 4
CH5 C2H~5 H30 + CH 3OH2 t-C4 H4 NH +
527 665 706 761 807 840
H 20 CH 30H i-C 4Hlo NH 3
Other popular reagent gases are isobutane and ammonia which are "softer" reagent gases because they do not ionise all organic molecules and induce less fragmentation. When chemical ionisation occurs by proton transfer to the analyte from an acidic reagent ion, the exothermicity of the proton-transfer reaction determines the internal energy of the protonated molecular ion and hence the extent of fragmentation: M + [B + HI+ - [M + H]+ + B The exothermicity of the proton-transfer reaction is directly related to the proton affinity. From a series of proton affinities, as shown in Table 6.2 for a few reagent gases, the appearance of CI mass spectra is roughly predictable [4]. For instance, a protonated molecular ion produced via isobutane ionisation is expected to possess less internal energy than that formed with methane. There are two reasons to explain the suitability of CI-MS for the confirmation of the molecular weight of an analyte. It appears that more than about 400 kJ/mol of internal excitation in the "quasimolecular ion" [M + H]+ is uncommon, even when methane is used as the reagent gas. The consequence is that relative abundant ions appear in the molecular ion region. With labile molecules, the exothermicity of the ionisation can be reduced by selecting a softer reagent gas. In addition, the even-electron [M + H] + ions possess an inherent stability compared with the radical M + ions produced with El. 6.4.2
Negative ions
The highly energetic electrons emitted from a filament generate, under El conditions, only small abundances of negative ions. Under CI conditions, 281
H.-J. Stan however, they lose energy by promoting positive ion formation and by colliding with neutral gas molecules. The low-energy electrons produced can interact with a sample molecule AB by three different mechanisms: AB + e -+ AB'AB + e - A' + B-
(resonance capture) (dissociative resonance capture)
AB + e -* A + + B- + e
(ion-pair production)
"Near-thermal" electrons of very low energy (- 0 eV) can undergo resonance capture, assuming that AB possesses a positive electron affinity. With an additional large cross-section for electron capture of AB, such negative-ion spectra can exhibit an increase in sensitivity of orders ofmagnitude above those found with other ionisation techniques. However, it should be noted that the extraordinary sensitivities can only be achieved under most favourable conditions with respect to the chemical structure of the analyte molecule. On the other hand, this source of information is available with all CI measurements provided the instrument is capable of detecting negative ions. The most favourable equipment allows the alternate measurement of positive and negative ions in one chromatographic analysis virtually simultaneously. Electron capture NCI (ECNCI) generates negative molecular ion radicals with low internal energy but with the inherent instability of an odd-electron ion. Therefore, the abundance of the molecular ion depends on the overall resonance stabilisation possibilities in the molecule. Often, an abundant stable anion constitutes the whole mass spectrum. In contrast to ECNCI, negative CI may be performed by applying special reagent gases. Br6nsted bases play a role analogous to that played by Bronsted acids in generating positive ions. For instance, CH3 0- can act as a Brdnsted base, producing [M - H - ions by abstracting a proton from the sample molecule. The ionisation technique generates even-electron molecular ions of low internal energy with little fragmentation tendency. Therefore, the [M - H]- quasi-molecular ion frequently constitutes the base peak [5]. Since the reagent gases are not as easy to handle as those for the PCI and ECNCI, the method is not very popular yet although it has obvious merits in many applications. 6.5
COMPLEMENTARY INFORMATION
The information of mass spectra obtained from the same compound with different ionisation methods is of a complementary nature. With EI, a parent 282
GC-MS. I: Basic principles and technical aspects of GC-MS ion is formed in the ionisation process possessing an inherent instability because of being a radical or odd-electron ion. Therefore, subsequent fragmentation is common, providing structural information. The abundance of the molecular ion, however, may be weak. CI is credited with providing molecular weight information because the formation of even-electron parent ions in a gas phase reaction with proton transfer in the form of "quasimolecular" ions [M + HI + is the dominating mechanism. These even-electron ions are mostly so stable that only little fragmentation is observed. The different exothermicity of the proton transfer may, however, lead to a different appearance of the mass spectra. With methane as the reactant gas, two more ions indicative to the molecular weight, namely [M + 29] + and [M + 41]+ , are usually observed, making the identification of the quasi-molecular ion even more reliable. With ECNCI, negative odd-electron molecular ions are formed with subsequent fragmentation, which frequently results in simple mass spectra dominated by a few ions. With organophosphorous pesticides, often only one fragment ion originating from the organophosphate group is observed, indicative of the subclass of organophosphates as diethyl- or dimethyldithiophosphate [6,7]. To demonstrate the complementary nature of the information provided by the three ionisation methods, two examples are chosen from the organophosphate insecticides, the pesticide group systematically investigated [6,7]. In Fig. 6.7, the three spectra of dicrotophos are presented. The EI spectrum is dominated by the base peak indicative of dimethylphosphates, which show either m/z 93 ((CH3 0) 2PO) or m/z 127 ((CH 3 0) 2PO2 + H) if hydrogen rearrangement is favoured with the side chain, as is formed with dicrotophos. The molecular ion at m/z 237 and a fragment ion at m/z 193 (M-(CH 3) 2N) exhibit low abundances. In trace analysis, these two ions may not reliably be observed. With PCI, the mass spectrum exhibits an intense "quasi-molecular" ion [M + H]+ and the two adduct ions [M + 29] + and [M + 41] + at m/z 238, 266 and 278, respectively. Two fragment ions at m/z 112 and 193 are indicative for the structure of the side chain as indicated. With ECNCI, the mass spectrum of dicrotophos contains only a few negative ions with the base peak at m/z 125 dominating and indicative of the dimethylphosphate group. The fragment ion at m/z 222 denotes the loss of a methyl group. All three fragment patterns "puzzled" together obviously give information that is sufficient to identify the pesticide as dicrotophos. A second example is given with the three spectra of bromophos shown in Fig. 6.8. Although it belongs to the parathion group, whose members usually exhibit intense molecular ions due their aromatic structure, M+ cannot be observed with bromophos. The concentration of three halogens at one phenol 283
H.-J. Stan dicrotophos
El
Abundance
127 l
90 80 70 60 50 40 30 20 10
67 193 55
,,
n
40
III/L--
60
.. 4.. .1.I109
80
160.
237
221
100 120 140 160 180 200 220 240 260 280 300 320 340 360 380 PCI
Abundance
ma_ b
93R v
90 80 70 60 50 40 30 20 10 57 7 2 6(0
80
112 266
193
98
1L
140
100
120
140
1278
I 160
l
Am
180 200
-
r
220 240 260
r
7
7
-
'
.
.
280 300 320
-
I
'
340
ECNCI Abundance
125
90 80 70 60 50 40 30 20 10 IILZ-->
u·
79 6C)
80
1
100 120
141 222 .
L
i I
140 160
180
200 220 240
260 280 300 320 340
Fig. 6.7. Mass spectra of dicrotophos measured with different ionization conditions. Top: EI, middle: PCI, bottom: ECNCI. moiety facilitates the expulsion of a chlorine atom radical, as already seen with 2,4-D in Fig. 6.5. The M-CI fragment constitutes the base peak in the EI spectrum and shows the typical CIBr isotope cluster (see Fig. 6.3). The other intense fragments from m/z 125 to 63 all arise from the dimethylthiophosphate moiety with (CH30) 2 PS at 125, (CH30) 2PO (after rearrangement!) + at 109, (CH30) 2 P at 93, etc. In the PCI spectrum, the [M + H] at m/z 365/367/369/341 exhibits the expected isotopic cluster of CI 2Br as well as 284
GC-MS. I: Basic principles and technical aspects of GC-MS bromophos
El
Abundance
331
90
80 70 60
so50
125
40
30 20 10
79 63
93 143
60
2413
1
3166
80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380
Abundance 90 80 70 60 50 40 30
125
l l 93~~.w. IILU
20 10 mFz--
PCI
367
100
V50
395 287
I·L 150
L · ·
··
200
331
LII · 311~1
· ·I 250
300
350
400 ECNCI
Abundance
257
90 80 70 60 50 40 30 20 10 M/z-->
0 60
270 79 2222
316 330 351
80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380
Fig. 6.8. Mass spectra of bromophos measured with different ionization conditions. Top: EI, middle: PCI, bottom: ECNCI. the two satellite peaks IM + C 2H5]t and [M + C 3H ]5 + . Loss of bromine results in m/z 287, loss of HCI in a small cluster at m/z 329 (base peak in the EI spectrum!). The fragments at m/z 125 and 111 (CH 3 0) 2 PO + 2H] originate
from the dimethylthiophosphate group. The ECNCI spectrum consists of only
285
H.-J. Stan two abundant ions. The base peak is formed by a rearrangement, common with the parathion group, resulting in the thiophenolate with the complete halogen substitution retained, as can be drawn from the isotopic cluster. The other ion is obviously formed from the M- by loss of bromine and methyl, as can be deduced from the m/z 270 and the isotopic cluster. Noticeable is the tiny peak at m/z 141 indicative of the dimethylthiophosphate group. This fragment is usually base peak with other members of this class not belonging to the parathion group but containing an alkyl side chain comparable with dicrotophos, for example. Summarising, the molecular weight information is provided with PCI, the assignment to the dimethylthiophosphates with EI and the affiliation to the parathion group with ECNCI. The presence of two chlorine and one bromine atoms is indicated by the isotopic clusters of the ions formed with all three ionisation methods. The application of ECNCI-MS in combination with other detection methods in GC parallel to GC-MS is described in section 6.13. 6.6
HIGH-RESOLUTION MASS SPECTROMETRY (HRMS)
HRMS enables the measurement of the exact mass of an ion and thus an unequivocal identification of its elemental composition. This high resolution can be achieved with double-focusing mass spectrometers or FT-ICR instruments. The usefulness of elemental composition information increases with increasing mass and this requires also an increase in mass-measuring accuracy. The technique is of great importance in basic research when unknown chemical structures are to be elucidated. In environmental analysis, the combination GC-HRMS is applied to ultra-trace analysis of polychlorinated dioxins (PCDDs). In Table 6.3, possible interferences for the most important chlorinated dioxin, namely 2,3,7,8-tetrachlorodibenzo-p-dioxin TABLE 6.3 Application of HRMS for separation of possible interferences of 2,3,7,8-TCDD Compound
Formula
Mass of interfering ion
2,3,7,8-TCDD Heptachlorobiphenyl Nonachlorobiphenyl Tetrachloromethoxybiphenyl DDT DDE
C1 2H40 2C14 C12H3C1 7 C12HC1 9 C1 3H8OCl 4 C14HgC 5 C14H8 C14
321.8936 321.8678 321.8491 321.9299 321.9292 321.9292
286
Resolution needed
13,000 7300 8900 9100 9100
GC-MS. I: Basic principles and technical aspects of GC-MS (2,3,7,8-TCDD) are compiled. When using the common low-resolution mass spectrometry (LRMS) with GC coupling, it would not be possible to distinguish 2,3,7,8-TCDD from the other compounds listed in Table 6.3 if the principal ion m/z 322 was monitored in selected ion monitoring (SIM) mode [8]. When applying LRMS, it is definitely necessary to resolve these interferences by chromatography. Otherwise, if any of these compounds coelutes with 2,3,7,8-TCDD, false positive identification may be obtained. The other problem is to avoid false negative results that may arise from the coeluting interference that makes the mass to intensity ratio of the indicative ions m/z 320, 322, and 324 incorrect. Since the residue analysis of PCDDs is carried out to monitor femtogram amounts, GC-MS in SIM mode is the only method for achieving the detection sensitivity needed. Positive or negative results cannot be proved by another analytical technique and the results are of great public concern. This is the reason why official methods demand the application of GC-HRMS. 6.7
TANDEM MASS SPECTROMETRY (MS/MS)
The structural information provided by mass spectrometry can be further enhanced with the combination of two mass spectrometers in one instrument adding a new dimension. This technique allows the measurement of the fragmentation of a selected peak in a mass spectrum producing the product (daughter) mass spectrum of that selected (parent) ion. The first mass spectrometer is used as a separating device for mixtures (such as unresolved peaks in GC-MS or LC-MS); after separating one particular ion, energy is added to yield dissociation product ions that are then separated in the second mass analyser. This mass spectrum is then used for structural characterisation of the selected (parent) ion. While in theoretical research this method is used to investigate the structure and stability of a molecule's fragment ions, in residue analysis the technique can be applied to the molecular species produced by soft ionisation methods such as CI. As described, PCI produces [M + H]+ usually with little fragmentation, which is useful in molecular weight determination but provides no structural information. In the instrument first used for MS/MS measurements, three quadrupoles are combined to the so-called "triple quad" with the first quadrupole as the separating device for the [M + H] + ions and the third as the mass analyser to monitor the products of the dissociation process. This dissociation is induced by collisions with a target gas that takes place in the central quadrupole and is referred to as collision activation (CA) or collision-induced dissociation (CID). Such CID mass spectra are as indicative for the structure or identity of 287
H.-J. Stan a compound as common EI mass spectra. The MS/MS instrument can in the same way be combined with GC and LC just as a normal mass spectrometer, making it the most sophisticated tool in pesticide residue analysis. Since the instrument is fully under computer control, it is possible to perform special techniques. Tandem MS can be carried out principally in two ways: consecutive in space by using two separate spectrometers (multiple-sector or multiplequadrupole instruments) or consecutive in time by using the same mass resolving system twice (ion traps or less frequently in pesticide residue analysis in FT-IRC) [9-121. Consecutive separation in space is easier to understand and is schematically shown in Fig. 6.9. A mixture of compounds is ionised and separated in the mass analyser MS 1. Only one (parent) ion is transmitted into the collision cell where the CID takes place. The resulting fragment ("daughter" or "product") ions are separated in mass analyser MS 2. Note that by selecting monoisotopic ions only monoisotopic daughter ions are produced. The daughter ion spectrum is, therefore, devoid of isotopic clusters. The basic equation describing the formation of a daughter ion md+ from a parent ion mp+ by loss of a neutral mn is mp +
md+ + mn
The parent ion is selected in MS 1, the daughter ions are detected in MS 2, and mn is inferred from the difference. Each of these three species can be designated as the independent variable in MS/MS measurements; the relationships are summarised in Table 6.4. The most simple reaction in MS/MS is the dissociation of a parent ion into daughter ions and neutral fragments. This is referred to as product (daughter) ion scan and provides, with a full product ion spectrum, the greatest information. To achieve the lowest possible detection limits for a target compound in product ion MS/MS, single-reaction monitoring (SRM) is performed. In this technique, all variables, as shown in Table 6.4, are fixed. This means that the first mass analyser is set to transmit the parent ion and the second mass analyser is set to transmit a specific daughter ion. This SRM technique is analogous to single-ion monitoring used in GC/MS when asking for the lowest possible detection limit in SIM mode. SRM in GC-MS/MS and LC-MS/MS is a means of eliminating "chemical noise" in the MS/MS spectrum. This technique is of outstanding importance for the analysis of pesticides with LC-MS in real food samples, as described in chapters 8 and 9. Although it is apparent that SRM offers less information than a complete MS/MS spectrum, it nonetheless provides a considerable increase in 288
GC-MS. I: Basic principles and technical aspects of GC-MS Al A2
Mixture of Analytes
A3 A4
1
I P3 P2 P1
P4 Mass spectrum of Parents
I Collision Cell
I P3+
Daughter Fragments of P3
Fl F2 F3 F4 F5
I
P3 F3 F2
F5 F4 Daughter mass spectrum
Fig. 6.9. Schematic of the principle of tandem MS (MS/MS).
specificity over a single-stage mass spectrometric analysis. Notice that the generation of a peak in a GC-MS/MS analysis in SRM mode requires that three independent criteria be met: retention time, mass of the parent ion, and mass of the product ion must satisfy the selected values. In pesticide multiresidue analysis, not just one such SRM measurement has to be performed in 289
H.-J. Stan TABLE 6.4 Parameter setting in MS/MS measurements Scan
mp+
md+
mn
Product (daughter) ion scan Precursor (parent) ion scan Neutral loss scan Single-reaction monitoring
Fix Vary Vary Fix
Vary Fix Vary Fix
Vary Vary Fix Fix
one retention time window but many of them can be repetitively carried out, which is referred to as multiple reaction monitoring (MRM). This is the most effective and popular way of performing pesticide multi-residue analysis in food samples with LC-MS/MS. A unique analytical aspect of MS/MS is the ability to screen rapidly for compound classes. Referring to the basic MS/MS reaction, any of the three species can be designated as the independent variable in an MS/MS experiment, as summarised in Table 6.4. If the product ion, md+ , or the neutral fragment, mn, is specified as the independent variable, new information is available that is provided by no other analytical technique. This technique, however, is not of great importance for pesticide residue analysis because the target compounds, namely pesticides, are known and belong to a multitude of compound classes. Measurements in which md+ is the independent variable are known as parent (precursor) ion scans. If a compound class includes a particular substructure which forms a very stable ion, parent ions derived from members of this class tend to produce a common daughter ion with this substructure. With MS 2 fixed to that daughter ion and MS 1 scanned, all parent ions can be detected. This technique also is of limited use in pesticide residue analysis. MS/MS experiments as described are performed with triple quadrupole instruments where, after separation of a certain parent ion in a first quadrupole, the CID takes place in a second quadrupole or octopole which serves as a collision cell. The resulting product ions are finally measured in the third quadrupole. This arrangement of tandem MS is mostly described as MS/MS in space. MS/MS can also be carried out with ion-trap instruments where all these experimental steps occur in the same space of the ion trap but one after another, and this is therefore designated as MS/MS in time. In the first step, the precursor ion is isolated and accumulated in the trap while all the others ions are ejected, then the isolated precursor ion is accelerated and collides with the helium gas in the trap and fragments to generate the product 290
GC-MS. I: Basic principles and technical aspects of GC-MS ions which then are ejected to generate a mass spectrum. The difference between ion-trap instruments and triple quad instruments is that, with ion traps, only product ion scans are possible but not parent ion or neutral loss scans. However, this must not be considered as a major drawback, these two techniques having no real value in pesticide residue analysis. On the other hand, ion-trap instruments are capable of performing MSn experiments or multi-stage MS, which means that a product ion can be retained in the trap and again allowed to collide to obtain another set of product ions. This process can be sequentially automated so that the most abundant ion from each stage of MS is retained and fragmented by collision. This is a very powerful technique for determining the structure of molecules such as peptides but until now it has rarely been applied to pesticide residue analysis.
6.8
MULTI-RESIDUE SCREENING FOR PESTICIDES APPLYING GC-MS
6.8.1 Introduction to multi-residue screening for pesticides with GC-MS Over the last few decades, multi-residue screening procedures for more than 400 thermostable pesticides in food samples have been based on gas chromatographic determinations. Results obtained with popular selective detectors such as ECD, NPD, FPD or the element-specific AED required confirmation by GC-MS [13-16]. GC-MS has dominated confirmatory analysis in the pesticide field since the early days. This technique has greatly benefited from the development of fused silica capillary columns and the development of small, relatively inexpensive mass spectrometers as dedicated gas chromatographic detectors. GC-MS is now readily available to residue chemists and the ease of operation and maintenance make specialists in MS no longer a prerequisite for GC-MS operation as with the more complex instruments of earlier generations. Positive identification of low-level residues in a food sample presents the analyst with a number of problems. Full-scan spectra should be obtained wherever possible. The high sensitivity and selectivity of modern GC-MS instruments enables this in almost all situations to below 0.01 mg/kg depending on the matrix and, in particular, on the chemical structure of the pesticide. With most instruments, full-scan spectra can be evaluated at the low ng level, i.e., 1 or 10 pg analyte injected into the GC-MS system with the sample. This can be achieved with extracts from food samples applying
291
H.-J. Stan a minimum clean-up. Spectral averaging and background subtraction facilities provided by the data system are generally used to remove contributions from matrix background or partially resolved contaminants. However, with very weak spectra, these data-processing procedures may lead to corrected mass spectra of dubious validity. This is the point where the analyst has to change from full spectral scanning to selected ion monitoring using the reduced number of mass channels with the considerably improved detection limits for the specified target compounds ions. In the following section, the application of GC/MS for the screening for pesticides in food with full scan as well as target compound analysis applying SIM is reviewed. The same methods are also applied for the confirmation of positive results from screening methods using less selective detectors. 6.8.2
The GC-MS instrument
Capillary GC is the analytical method with the greatest separation power. MS is the most sensitive method of molecular analysis with the potential to yield information on the molecular weight as well as the structure of an analyte. When these two methods are directly combined into one GC/MS system, the capabilities of that system are not merely the sum of the capabilities of the two outstanding analytical methods; the increase in analytical information is exponential. Extreme selectivities can be obtained, which are of utmost importance in screening analysis of target compounds in food as well as in environmental samples. The enormous amount of data generated by the GC-MS system in one single analysis makes a dedicated computer an integral part of the instrument. Automated analysis is routine in GC with food samples. Autosamplers carry out automatic injection in splitless, programmed temperature vaporiser (PTV), large volume injection (LVI) or any other mode fully controlled by builtin software [15,16]. Recently, difficult matrix introduction (DMI) injectors and special on-line sample preparation interfaces have been introduced, which appear very promising with respect to the reduction of the time necessary for clean-up [17]. An example is given in section 6.13. The enormous amount of data generated in each GC-MS analysis is stored in data files, usually on a hard disk. In this way, sample throughput can be maximised by round-theclock instrument operation. The analyst is no longer dedicated to instrument operation but confronted with a vast amount of analytical data. In screening analysis, it is highly desirable at least to be able to select positive or possibly positive samples from those certainly free of residues of pesticides or other 292
GC-MS. I: Basic principles and technical aspects of GC-MS target compounds. This is achieved by dedicated software programs for automated evaluation of full-scan as well as SIM analyses. 6.8.3
The mass spectrometer
When a molecule is ionised in a vacuum, a characteristic group of ions of different masses is formed. When these ions are separated, the plot of their relative abundances versus mass constitutes a mass spectrum. The emergence of such a mass spectrum and the information that can be drawn from it have been described in the preceding section. Mass spectrometry can be divided into two fundamental processes: ionisation and mass separation or filtering with subsequent recording of the ions formed. The recorded ions are finally subject to data processing by means of computers. The mass spectrometer is nowadays a highly sophisticated instrument under full computer control. It basically consists of five parts: sample introduction, ionisation, mass analysis, ion detection, and data processing. 6.8.3.1 Sample introduction Sample introduction in capillary GC-MS is simply performed nowadays by conducting the end of the fused silica column directly into the ion source through a heated transfer line. Modern mass spectrometers are equipped with efficient pumps to cope with the flow of up to 20 m/min carrier gas from the column, values commonly encountered with wide-bore capillary columns. Narrow-bore columns, however, are usually operated with a carrier gas flow of less than 2 ml/min. 6.8.3.2 Ionisation The analytes may be ionised in a number of ways but, for automated screening analysis, only electron ionisation is in common use although special applications of target analysis with other ionisation techniques are possible. The various ionisation methods employed in pesticide residue analysis are reviewed in the preceding sections. 6.8.3.3 Mass analysers After their production in an ion source, ions are analysed according to their mass-to-charge ratio (m/z) in a mass analyser. Five types of mass analysers are currently available: the magnet sector, quadrupole mass filter, ion trap, time-of-flight (TOF) and ion cyclotron resonance instruments. Over the last three decades, quadrupole and ion-trap instruments have dominated 293
H.-J. Stan the pesticide residue analysis field. Recently, however, TOF instruments have been successfully combined with gas chromatography enabling, in particular, with the appropriate columns, much faster GC-MS analyses. Magnetic sector instruments All the early work in organic MS as well as the pioneering work in GC-MS by coupling packed columns to an ion source by means of special interfaces, which preferentially removed carrier gas molecules and transferred the analyte molecules to the ion source, were performed with magnetic sector mass spectrometers. An electromagnet is used to separate ions for subsequent mass detection. In a single focusing sector instrument, the ions with mass m and z elementary charges are accelerated towards the source exit slit with a great deal of energy by means of the accelerating voltage in the source and fly through the magnetic field, which focusses ions of a particular m/z ratio into a narrow beam at a slit just prior to the detector. By variation of the magnetic field (or the accelerating voltage), ions of different m/z values pass through and can be detected by a detector at a fixed position as being separated in time. The most common way of scanning is by an exponential magnet scan allowing equal dwell times for all individual masses within the scan. The resolution of the mass analysis can be improved by means of an electrostatic analyser, which provides an additional focus to the ions. Instruments where both a magnetic and an electrostatic sector are coupled are called double-focussing mass spectrometers. These are capable of high-resolution mass determination separating different ions with the same nominal masses and are mainly used for elucidation of chemical structures of unknown compounds. In food analysis and in particular in routine pesticide residue analysis, these instruments are rarely in use. They are, however, state of the art in the trace analysis of polychlorinated dibenzodioxins and dibenzofuranes. Quadrupole instruments The quadrupole mass analyser is actually a mass filter. It consists of four hyperbolic rods that are placed parallel in a radial array. Opposite rods are charged by positive or negative DC voltage upon which an oscillating radio frequency is superimposed. Ions are introduced into the quadrupole field by means of a low accelerating potential of typically 10-20 V. They start to oscillate in a plane perpendicular to the rod length. When the oscillations are not stable, the ions do not pass the filter because the amplitude of the oscillations becomes infinite. When stable trajectories are made, the ions are transmitted towards the detector. The quadrupole filter thus acts 294
GC-MS. I: Basic principles and technical aspects of GC-MS as a band-pass filter, usually set to transmit ions of one particular m/z ratio ("unit-mass resolution"). To obtain a mass scan, the DC and radio frequency voltages are varied while their ratio is kept constant. The mass permitted to pass through is linearly related to the amplitude of the voltage. This simplifies GC/MS operation as well as computerisation. The linear relationship between mass and voltage makes control and calibration by computers easy. Quadrupole mass spectrometers have a reputation for high sensitivity and the ability to scan rapidly at millisecond intervals. These qualities made them well suited for coupling with capillary GS to scan the narrow peaks produced. At the present moment, the quadrupole mass filter is the most widely applied mass analyser in GC/MS as well as in LC/MS. Ion-trap detectors The ion trap was developed as a quadrupole-related detector for capillary GC. The unique feature of the ion trap compared with conventional mass spectrometers is that the ion source and analyser region are the same. In recent years, instruments with a separate ion source have also been developed. Ion traps are operated at relatively high pressures (0.1 Pa of He). Molecules entering the trap are ionised by conventional electron impact. Ions over the entire m/z range of interest are not allowed to leave; they are trapped by a quadrupole field, which is formed between end-cap electrodes and a ring electrode by applying a radio-frequency voltage. By raising the RF potential, the trajectories of ions of successive m/z values are made unstable. Unstable ions will rapidly depart the trapping field region in the direction of the end-cap electrodes, and since the lower end cap is perforated, a significant percentage will be transmitted through and are detected by an electron multiplier. Detection limits reached with the ion-trap detector have been reported to be better than with any other mass spectrometric detector in fullscan mode but there is not the increase in detection sensitivity in SIM mode that is observed with quadrupole or magnetic sector instruments. Mass spectra generated by an ion trap in earlier instruments were not always identical to those from conventional quadrupole mass spectrometers, although differences were generally not great. The reason was that the pressure in the ion trap is higher than in a conventional ion source forming (M + 1)+ ions from addition of H+. This ion-molecule reaction resembles production of pseudo-molecular ions in chemical ionisation. Therefore, under certain conditions, EI mass spectra might have contained a few additional ions resulting from the chemical ionisation process. Improvements in the computer control of the ionisation process have reduced the ion-molecule reactions such 295
H.-J. Stan that "mixed EI/CI mass spectra" no longer are recorded under conditions of routine GC/MS analysis. Time-of-flight (TOF) instruments In a TOF mass spectrometer, a pulsed beam of ions is accelerated by a potential into a flight tube and the time needed to reach a detector is measured. The ion source is pulsed in a way that a full mass spectrum is recorded before the first ions of the next pulse arrive at the detector. A rate of 5-40,000 pulses per second are usual. Depending on the acceleration voltage, 100-200 jts are necessary to record a complete spectrum. At least 10 of the acquired transients are summed prior to storing, which brings the number of mass spectra stored at present to a maximum of 500 per second. At higher data-acquisition rates, however, the apparent detection sensitivity of the instrument decreases due to the ion statistics. If the TOF-MS system is pulsing ions into the flight tube at the same rate of 5000 transients per second for the acquisition of 10 spectra per second, 500 transients are summed for each spectrum while, for the acquisition of 100 spectra per second, only 50 transients are summed for each stored spectrum. The greater number of transients summed at lower acquisition rates improves the signal to noise (S/N) ratio and, therefore, the sensitivity. One important characteristic of all TOF instruments is high ion transmission. Consequently, detection limits of TOF-MS are expected and reported to be better than that of quadrupole MS. The resolution has long been limited, although impressive improvements in this respect have been achieved recently by using reflectrons. This type of TOF mass spectrometer has been extensively used in studies with plasma and laser desorption techniques on large molecules such as proteins. Recently, it has also been interfaced to gas chromatography and liquid chromatography. Two aspects have been emphasized: improved resolution with the capability of exact mass measurement providing elemental composition data for both molecular and fragment ions and also fast data acquisition with high-speed data-collection systems capable of obtaining up to 500 full-range mass spectra per second. In fast gas chromatography, such a detector allows handling of narrow peaks of a width of 100 ms at the base, adequate for the generation of a pattern of sufficient data points for accurate recognition of the retention time and precise peak-area calculation. The new possibilities to automatically deconvolute full mass spectra with new algorithms to provide clean mass spectra from co-eluting compounds on the basis of minimum retention time differences appear even more promising. These algorithms were developed by Stein [18] at the National Institute of Standards (NIST) and incorporated 296
GC-MS. I: Basic principles and technical aspects of GC-MS into a Microsoft Windows program called AMDIS (automated mass spectral deconvolution and identification system). The principles of AMDIS are described in section 6.9.7.
Fourier-transformion cyclotron resonance (FT-ICR) instruments In a Fourier-transform ion cyclotron resonance mass spectrometer (FTICR/MS), the mass analysis is performed in a cubic cell placed in a magnetic field. The cell consists of two opposite trapping plates, two opposite excitation plates, and two opposite receiver plates. Ions are trapped in the cell in cyclotron motions and can be excited by means of a radio-frequency pulse to move them in phase on increased circle radii. The coherent movement of the ions generates an image current in the receiver plates that finally can be transformed by applying Fourier transformation into a regular mass spectrum. An important feature of FT-ICRMS is the extremely high resolution and sensitivity that can be achieved. The cell must be placed in relatively high vacuum (10 - 7 Pa). Although interfacing to a gas chromatograph has been reported, the domain of the high-cost instrument is basic research rather than analysing real-life samples. The choice of the analyser depends on the application. In practice, most GC-MS instruments have been developed on quadrupole including ion-trap technology. This choice is mainly determined by the simplicity of construction and vacuum technology and consequently the cost and space requirements. The situation, however, is changing and TOF instruments will play an increasing role.
6.8.3.4 Ion detection All mass spectrometers that are easily interfaced to a gas chromatograph are nowadays equipped with an electron multiplier. In such an electron multiplier, the ion beam is converted to an electron beam that is subsequently amplified through a cascade effect. In analogue detection, the signal of the multiplier is converted to a voltage, further amplified, and finally converted into a digital signal that can be processed by a computer. Usually, the electron multiplier is constructed to detect positive ions but, by placing a conversion dynode in front of the electron multiplier, negative ions can be detected, too. Upon impact of negative ions, the conversion dynode produces positive ions, which are amplified as described. TOF instruments are equipped with microchannel plate detectors working on a similar principle but with a very high time resolution. 297
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6.8.3.5 Data acquisition and processing (handling) Modern GC-MS systems produce an enormous amount of data that is acquired using standard personal computers. The operation of the mass spectrometer, data acquisition and processing is fully executed and controlled by the computer. Additionally, the interpretation of the data is also to a considerable extent carried out with the computer, especially in the form of automated library searches against reference spectra compiled in dedicated libraries. The provision of a powerful macro language with some software packages allows the creation of individual software solutions for the support of automated screening procedures. Two modes of operation are in common use and are applied to automated screening analysis of pesticide residues: repetitive scanning, also described as cyclic scanning or full-scan mode, and SIM. In full-scan mode, data are acquired by continuous repetitive scanning of the GC column eluate over the full analysis time starting after the solvent peak has been passed. The rate of scanning is predetermined by the operator; usually values in the range of 0.5-1 s per scan are used with capillary columns but, with shorter columns and faster gas chromatography, higher scan rates may be necessary to obtain accurate peak profiles from narrow fast gas chromatographic peaks as a prerequisite of reliable quantification. With modern quadrupole instruments, scan rates up to 20 per second are possible but, at higher scan rates, the apparent detection sensitivity of the instrument decreases because the S/N ratio depends on the dwell time of the acquisition of the individual ions. Therefore, a scan rate of 10 per second seems the acceptable limit in pesticide trace analysis. The dependence of apparent detection sensitivity on the acquisition rates is also valid with TOF instruments, but at a different level as described. The greater number of transients summed at lower acquisition rates improves the S/N ratio and therefore the sensitivity. Independently of the way the data are collected, each scan results in a full mass spectrum that is stored separately in the computer memory. Basically, a three-dimensional data array is generated by repetitive scanning with time, m/z and ion intensity as the three dimensions. This data array can be processed in various ways. A section in the plane of m/z is called a mass or ion chromatogram. When the intensities of all ions in each spectrum are summed and plotted as a function of time, a total ion current (TIC) chromatogram is obtained. In GC/MS, this plot is used as the nonselective chromatogram to see all compounds in the sample amenable to gas chromatographic analysis. This chromatogram is often compared with those obtained with the universal flame ionisation detector.
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GC-MS. I: Basic principles and technical aspects of GC-MS Mass or ion chromatograms are here referred to as reconstructed ion chromatograms (RIC) in order to emphasize the fact that they are produced by reconstructing chromatogram-like ion intensity plots from separate mass spectra acquired in repetitive scanning and to distinguish them clearly from SIM.
6.8.3.6 Tuning and calibration The information that can be obtained from a mass spectrum fully relies on proper tuning and calibration of the instrument. Tuning is performed to achieve a high sensitivity over the whole mass scanning range and a proper mass resolution. The former tedious task of iterative adjustment to obtain the desired performance is nowadays automated employing software algorithms, which optimise the interactive lens potentials. The calibration of the m/z axis of the mass spectrum in EI is performed with reference compounds of which perfluorokerosine (PFK) and heptacosafluorotributyl amine (PFTBA) are in general use over the mass range relevant for GC/MS.
6.9 6.9.1
COMPOUND IDENTIFICATION Mass spectral libraries
Mass spectra obtained under standard conditions may be considered as a fingerprint of the molecule reflecting its chemical structure. They have therefore been collected in various mass spectral libraries. These libraries are commercially available for computer searching and identification of unknown compounds provided that a clean mass spectrum can be produced with the analytical procedure [19-24]. Excellent search methods for computerised libraries are available but the usefulness of these methods must not be overestimated with respect to elucidating the identity of unknown compounds in a food sample because only a minor portion of all known organic compounds are compiled in the universal mass spectral collections. In target analysis such as pesticide residue analysis, however, the situation is much better because all the peaks in a chromatogram are compared by means of their mass spectra with the entries of a limited mass spectral library containing only the target compounds, which means pesticides and their metabolites in this case.
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Background ions
A major problem in identification of sample peaks by means of their mass spectra is background ions. These may cause confusion in the interpretation of mass spectra. In electron impact MS, there are background peaks in the lower mass region at m/z 18, 32, 40, and 44 due to residual air. In GC/MS analysis, background ions may arise from column bleed of the separation phase and from the carrier gas. Since these background ions appear constantly over the whole gas chromatogram, they can easily be eliminated by background subtraction. Additionally, impurity peaks may arise from the sample preparation and clean-up; phthalates and other plasticisers are ubiquitous and practically unavoidable in trace analysis. The main problem with background ions in mass spectra of gas chromatographic peaks, however, arises from incomplete separation of the analytes from matrix compounds.
6.9.3
Background subtraction
Fortunately, computer background correction enables the removal of background ions from the analyte spectrum in most cases. The easiest way to clean up mass spectra is to subtract another mass spectrum which contains only background ions. Background ions are common to a larger number of mass spectra scanned at the base line of the gas chromatogram while ions due to a sample component exhibit abundances following chromatographic peak shapes with a maximum at the apex of the peak. The simplest type of subtraction involves a mass-by-mass subtraction of ion abundances of a background spectrum from the ion abundances at corresponding masses from the mass spectrum at the apex of the peak. Improved results can sometimes be obtained by averaging two or three spectra taken across the top of the GC peak, and subtraction of averaged spectra from both the leading and trailing edges of the peak. This method is of particular value in resolving overlapping peaks. Automated background subtraction methods can be used to remove interfering ions from overlapping matrix peaks as well as from non-separated target compounds. Automated background subtraction procedures are based on an algorithm that was introduced by Biller and Biemann as early as 1974 [25]. The procedure identifies all ions that maximise at each scan number and strips away all other ions from that scan. This stripping procedure not only effectively removes background ions from the column bleed and common matrix but also removes ions in a mass spectrum that originate from closely eluting unresolved GC peaks.
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GC-MS. I: Basic principles and technical aspects of GC-MS Modern GC/MS instruments have such a software routine for automated background subtraction at the operator's disposal. On the other hand, other methods of background subtraction, as described for manual evaluation, can be easily designed using macro language facilities. The effect of background subtraction in producing a clean pesticide spectrum from overlapping matrix compound ion peaks is demonstrated in section 6.9.5. A more computationally intensive approach to extract weak ion peaks by explicitly considering S/N values for the identification of those weak peaks has been elaborated recently and is described in sections 6.9.6 and 6.9.7. 6.9.4
Library search
The most important step in checking for pesticides or other target compounds is the possibility of an automated library search. When measured under standard conditions, the mass spectrum of a molecule is very indicative (like a fingerprint). By comparing the mass spectrum of the analyte with others in a reference file, the identity of its nature can be recognised. A useful feature of all computerised comparison algorithms is the calculation of factors which are used to distinguish between good, average and poor matches. A human would generally stop searching at the first good match, but a computer is usually programmed to find all matches above a given threshold of match factor and to report them in a rank list. A very efficient search method for the retrieval of good matches from a mass spectral library is probability based matching (PBM), first developed and refined by McLafferty and his group [26,27]. PBM incorporates the features of data "weighting" and "reverse search". The "weighting" involves the two principal parameters in mass spectra: masses and abundances. The probability of occurrence of most mass values varies in a predictable manner. The larger fragments tend to decompose to give smaller fragments. According to McLafferty and Stauffer [28], the probability of higher masses decreases by a factor of two approximately every 130 mass units. More important for the identification of components in mixtures or incompletely resolved chromatographic peaks is the second feature of PBM: by means of this, PBM ascertains whether the ions of the reference spectrum are present in the unknown spectrum, which may be a spectrum containing extraneous ions. The "reverse search" approach ignores ions in the unknown that are not in the reference spectrum, since these could originate from other components of the mixture. In a TIC chromatogram, all peaks can be recognised by means of an automated integration procedure provided by the instrument's software. Each peak consists of a number of full mass spectra, which can be individually 301
H.-J. Stan called up and applied to the library search with or without manual background subtraction. The library search can also be run fully automated, as will be described later. The performance of a library search routine should not be checked by theoretical considerations but only by its application to standard mixtures and spiked samples. Analysing standard mixtures with decreasing concentrations spiked to the variety of food matrices gives the analyst a measure of the instrument's detection sensitivity. In other words, he or she will learn which amount of a particular pesticide must be injected to obtain a positive identification with a full-scan spectrum. The limits of detection vary with the target compounds depending on their fragmentation behaviour. This includes both the abundances of the molecular ion and of fragment ions in the high mass region as well as the presence of isotopic clusters. The detectability, however, also depends considerably on the food matrix and on the chromatographic properties of the compound: good GC is a prerequisite for reliable results in trace-level residue analysis with GC-MS. 6.9.5 Manual verification: use of RIC with background subtraction Library search results can show poor hit quality but excellent correlation in the retention times for the peak searched and the suggested library compound. In this case, the target compound may be overlapped by a co-eluate from the matrix and, therefore, a manual evaluation must be performed. In many cases, such a manual verification procedure allows the confirmation ofthe identity of a compound generating a peak overlapped by the peak of a matrix compound. The prerequisite is that the target compound ions and the ions belonging to the overlapping matrix compounds do not elute exactly at the same time. This emphasizes again the importance of good chromatographic resolution in GC-MS. An example is given in Figs. 6.10-6.14. Shown in Fig. 6.10 is the TIC chromatogram obtained in full scan from an extract of oranges exhibiting a great number of large peaks all resulting from the matrix. Zooming in on a small portion of the TIC chromatogram provides the display in Fig. 6.11 where a number of peaks of co-eluting substances of different signal intensities are seen. Two positions on the chromatogram are indicated. The small peak at retention time 12.30 was recognised as a peak by the peak-finding algorithm and therefore it is a target of library search of all peaks in the pesticide library; it was identified as the internal standard used in our laboratory for pesticide residue analysis, namely ALDRIN. The second 302
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Fig. 6.10. TIC chromatogram of an extract of oranges. arrow points to the portion of the TIC chromatogram at retention time 13.24 where no peak can be spotted. At this retention time, parathion and chlorpyrifos are expected. RIC with three ions indicative for chlorpyrifos produce peaks which have their apex exactly at the same retention time, thus hinting at the presence of chlorpyrifos (Fig. 6.12). The mass spectrum in the apex looks like a typical mixed spectrum as found with matrix and gives, as expected, no positive result in a library search (Fig. 6.13). After background subtraction, however, a good match between the unknown and the library spectrum of chlorpyrifos was found with a quality of 70. As can be seen in Fig. 6.14, the mass spectrum from the extract is by no means free of ions originating from the co-eluting matrix but visual inspection confirms the presence of the molecular ion cluster and the relevant fragment ions in the sample spectrum. Note that the concentration level of chlorpyrifos was finally determined at 0.03 g/kg. As shown in the example, manual evaluation of peaks that exhibit a poor hit quality to relative proposed library compounds, but a good correlation in
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Screening for pesticides with full scan
Since a maximum tolerance of 0.01 mg/kg for almost all pesticides in at least one of the food commodities was established in the EU guidelines, this concentration level has become the standard for the evaluation of all analytical methods in the field of residue analysis. Recent improvements in mass spectrometric detection sensitivity allow for the presence of most of the more than 400 pesticides amenable to GC to monitor at this low concentration level with full-scan data acquisition when applying a suitable clean-up and extract concentration. 304
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The prerequisite for the recognition of an analyte in full scan is the appearance of an analyte peak in the chromatogram to start with the library search and background subtraction as described. Pesticides at trace concentrations completely overlapped by matrix compounds may be missed R."-n IRfi
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AMDIS from NIST
As demonstrated throughout this chapter, GC-MS is the method of choice for the identification of volatile (thermostable) pesticides in complex matrices from a wide variety of foodstuffs. The method can fail when acquired spectra are contaminated with extraneous ions, which commonly arise from co-eluting matrix compounds. The extraneous ions can pose a serious problem for automated target-compound identification methods where they can cause false negatives by reducing the spectrum match factor below some pre-set identification threshold. This uncertainty in the origin of ions in a mass spectrum may lead to a general loss of confidence in the reliability of making identifications of trace components such as pesticides in complex matrix extracts by GC-MS. 306
GC-MS. I: Basic principles and technical aspects of GC-MS In earlier methods, such as those of Biller and Biemann [251 and Colby [31], the extracted spectra are composed of all mass spectral ions that maximise simultaneously. These and other methods process an abundance data matrix consisting of ion/elution time pairs. Sets of ions whose abundances are correlated with one another are extracted but this approach is not able to make use of peak-shape information. A recent approach of Stein began with noise analysis for the recognition of component peaks at a very low signal level [18]. The algorithms were incorporated into a Microsoft Windows program called AMDIS (automated mass spectral deconvolution and identification system). The procedures include an integrated set of methods for first extracting pure component spectra (and retention data) from complex chromatograms and then using this information for the identification of target compounds in reference libraries. The methods were developed for a specific application, the automated identification of chemical weapons and related compounds, but they are expected to be applicable to any application requiring extraction of spectra from noisy chromatograms such as those obtained with pesticide residues in foodstuffs and the identification of target compounds by full spectrum matching. The overall data-analysis process involves four sequential steps: noise analysis, component perception, spectrum deconvolution and finally compound identification. The first step extracts signal characteristics from the whole data file of the chromatogram for later use in noise processing and threshold setting. The second step perceives the individual chromatographic components and determines a model peak shape for each component. The third step extracts purified spectra from the individual ion chromatograms using the model-shape approach, explicitly subtracting nearby components when necessary. The final step computes match factors for the extracted "deconvoluted" spectra with spectra in the reference libraries. In short, in the first step for each ion chromatogram, a noise factor is estimated which is then applied to indicate any possible peak which surpasses a calculated threshold. In the second step, components are perceived when a sufficient number of different masses maximises together. A precise maximisation time is computed by fitting a parabola to the maximum and its two adjacent scans. The measure of peak sharpness is computed for use in component detection. The model shape for each perceived component is then used for deconvolution. Finally, a hit list of library spectra ranked in similarity to the target compound spectrum is produced with a computed match factor, which ideally should reflect the similarity of the mass spectrum of the extracted compound and the reference compound from the library. 307
H.-J. Stan The application of AMDIS to deconvolute peaks in a chromatogram obtained with GC-TOF-MS is described later in section 6.13. 6.9.8
Confirmation and quantitative determination with SIM
SIM is a measurement method which changes the mass spectrometer into a highly selective detector tuned to monitoring of a small number of mass channels. The high gain in detection sensitivity with quadrupole instruments more than compensates for the reduction of structural information. The reduction of structural information caused by measuring only three ions instead of whole spectra is sometimes overestimated because mass spectral identification is based on various criteria. Reproducibility of retention times of better than 0.1 min is easily achieved with capillary columns that provide the highest chromatographic separation power of all chromatographic techniques, and can be additionally checked with internal standards. All three ions must give rise to a peak at the retention time corresponding within the reproducibility margin with the reference compound. Furthermore, the appearance profiles should be uniform and clearly resolved from other sample compounds where they have ions in common. The three selected ions must also match in relative intensity. Correspondence at trace-level concentrations is considered as established if the maximum difference intensity ratio of indicative ions relative to the reference is less than 20% [32]. The relative ratios can be determined either as peak heights or more frequently as areas of the ion chromatogram peaks. The use of isotope peaks of chlorine for this comparison is also acceptable for confirmation of chlorinated pesticides. Ions selected for SIM confirmation must be intense in the mass spectrum and indicative; that means all ions prominent with the mass spectrometric background from column bleed and common environmental contaminants as phthalates and hydrocarbons should be avoided. Generally, ions with higher masses are to be preferred because of their statistically lower abundance in other compounds and consequently greater significance. Ions of lower mass can arise by fragmentation from many compounds with higher molecular weight. A molecular ion of sufficiently high intensity is usually the best-suited indicative ion as applied in the confirmation. The proof of suitability, however, is always the appearance of the ion trace in the appropriate time window. If the confirmation criteria are fulfilled, any of the three ion traces can be applied for quantification. Frequently, one ion trace is used as quantifier and the other two as qualifiers. Quantitation is best carried out with two 308
GC-MS. I: Basic principles and technical aspects of GC-MS spiked food matrix samples "bracketing" the estimated concentration level of the target pesticide and run before and after the target sample. Through this process, confirmation and quantification are performed in one analytical sequence. 6.9.9
Target compound analysis with SIM
The combination of high separation efficiency provided by modern capillary columns with tunable selectivity and high sensitivity provided by mass spectrometric detectors under SIM conditions has in recent years gained the reputation of being the most powerful tool in ultra-trace analysis. This is the analytical method frequently used for monitoring baby food or any other kind of produce grown under the various "bio" conditions with respect to the low maximum tolerances of 0.01 mg/kg established for these kinds of foodstuffs. The method takes advantage of SIM time window programming and the high reproducibility of retention times. More than 100 pesticides can be monitored and determined in one run. The application of target-compound analysis with SIM, however, exhibits an inherent limitation to those pesticides selected as targets for the monitoring. Whilst capable of detecting the residue of one pesticide at the low ttg/kg concentration level, since the method is transparent to all other contaminants, another heavy contamination in the mg/kg level is missed because the particular pesticide is not included in the analytical method. Another critical point is the possible shift of retention times causing target compounds to leave the retention time window which would produce false negatives. Therefore, the reliability of the chromatographic conditions must be carefully checked by running standard mixtures of the target pesticides together with each sample sequence including spiked food samples. Although the SIM chromatograms appear almost transparent to coextracting matrix compounds, it is a severe mistake to apply a SIM peak to quantitation of an analyte without having carefully checked the peak shapes and peak-area ratios of all indicative ions. Quantitation must be performed with the ion least interfered with by matrix compounds or with all three ions independently. The latter method additionally provides a good indication of interferences should one ion trace give a different result. An early multi-residue method based on SIM was developed and evaluated with recovery data for 189 pesticides in fruit and vegetables by Fillion et al. [33]. Residues were extracted from food samples with 309
H.-J. Stan acetonitrile and co-extractives were removed by a clean-up step on a charcoal-Celite mini-column. SIM analysis was performed time-programmed with retention time windows containing one target ion and two qualifiers for each target pesticide. Two injections were required per sample to cover all compounds. In the first group, 35 retention time windows and, in the second group, 20 retention time windows were programmed over an analysis time of more than 60 min to cover all the target pesticides. The method demonstrated acceptable performance for the analysis of the number of crops investigated, exhibiting limits of detection from 0.02 to 0.2 mg/kg depending on the compound. An equivalent of 4 mg of food sample was injected onto the gas chromatographic column. The drawback of this method, however, is the well-known fact that a few relevant pesticides cannot be monitored because they are completely retained by the charcoal treatment. Such pesticides are chlorothalonil, dicloran, diphenylamine, HCB and propanil. The method was later miniaturised and modified by substituting the charcoal-Celite mini-column with an activated carbon membrane, but the problem of retaining pesticides extracted from the food matrix and amenable to GC in the charcoal clean-up could not be convincingly solved [34]. With regard to GC-MS, however, the method demonstrated the capabilities of this kind of target pesticide residue analysis because recognition and quantification can be carried out in one analysis if a proper calibration is performed. This type of trace analysis has become very popular in environmental research and is supported by the manufacturers of GC-MS instruments by dedicated software packages. The same food sample can be analysed in parallel with a spiked one. The spiked food sample is used to check the GC-MS instrument's performance in the same sequence of analyses and allows calibration and quantification with the corresponding matrix. An example is given in Fig. 6.15 where chlorpyrifosmethyl is detected with three characteristic masses, namely 286, 288, and 125, of which the latter mass is found with many organophosphates such as tolclofos-methyl, parathion, and pirimiphos-methyl eluting immediately after chlorpyrifos-methyl. Although one mass is common to these pesticides, they can easily be distinguished by their characteristic masses, as shown with chlorpyrifos-methyl. A special approach is target pesticide analysis developed with SIM and time window programming but using an ion trap instrument applying full scan. Ion trap instruments do not provide the increase of detection sensitivity observed with quadrupole instruments because they always produce the full spectrum of ions. An example of such an analysis is presented in 310
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Fig. 6.16 showing the whole computer screen as produced by the Enhanced Data Analysis software of the HP ChemStation (Agilent). In window #6, which fills the upper part, the SIM ion traces are displayed selected for penconazole in this case. The right window shows a table with all the target pesticides in the SIM method. Those pesticides found by the search algorithm are marked with "x" in front of the name. A click on a pesticide name calls up the upper retention time window with the corresponding SIM traces and the name, retention time at the apex, the concentration according to the calibration performed, and the relative peak areas related to the quantifier ion, which is set to 100%. These peak area relations are automatically calculated with a corresponding calibration run. The parallel display of calibrated peak area relations and those in the sample together with the match of the retention time is the measure of the identity of the compound in the sample. In this example, however, the GC-MS data were generated with an ion trap instrument running in full scan, as already explained, and then transformed for this software developed for quadrupole instruments. This 311
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Fig. 6.16. Analysis of a mixture of pesticide standards in full scan applying SIM Enhanced Data Analysis software of the HP ChemStation (Agilent). results in a complete mass spectrum, as is presented in the left windows, with all the capabilities known from full-scan data processing including a library search from these windows where the mass spectrum is displayed and manual background subtraction in the window at the top right where the SIM traces are displayed, which are in reality RIC traces here. The result of such an analysis is shown in Fig. 6.16. A similar method was reported in 1995 by De Kok et al. [35,36], who applied the ion trap instrument GC-ITD (Varian Saturn), with software packages processing the data along the same lines as described, for the automated screening of a total of 320 pesticide residues in fruit and vegetables. At that time, the method had been evaluated for 2 years in the Food Inspection Service in Alkmaar (The Netherlands) with more than 2000 samples of fruits and vegetables. 312
GC-MS. I: Basic principles and technical aspects of GC-MS 6.10 AUTOMATED SCREENING APPLYING FULL-SCAN ACQUISITION Traditional screening analysis was always carried out with selected detectors such as ECD, NPD, and FPD followed by dedicated confirmation with GC-MS in full scan or SIM mode. The other method was target compound analysis with time programmed SIM window setting with the naturally imposed restriction on the number of pesticides monitored. Either method poses severe disadvantages. The combination of screening with selected detectors and additional confirmation of suspicious peaks is time-consuming. The application of target compound analysis with SIM exhibits the inherent limitation to these pesticides selected as targets for the monitoring method. Since more than 400 pesticides can be analysed by GC-MS and since most of them may be extracted and cleaned up with good or medium recovery applying standardised procedures, all these pesticides can be detected in a gas chromatogram if a suitable detection method is applied. Such a universal detection method is undoubtedly EI mass spectrometry when operated in full scan. Therefore, in recent years, the mass spectrometer, which had been used only in confirmatory analysis for decades, has also gained popularity in screening analysis. This new application has become the domain of quadrupole or ion trap mass selective detectors but they may be joined in the future by TOF instruments. In principle, any problem that can be solved using pen and paper or the keyboard of a computer in a finite amount of time by following logical rules can be performed by a computer. First, one needs to define clearly a set of rules for GC-MS data analysis. The key to the flexibility necessary for creating automated methods is to break down the data analysis problem into a number of small sequential tasks, each of which has associated software routines. These routines built up with a special macro language can then be linked together as needed to customise data analysis for individual samples with respect to target compounds. Considerable improvements in available software have been introduced in recent years for qualitative automated data analysis handled by powerful macro programming language, which enables links with standard text and spreadsheet programs for both processing and output. Since the optimum automated evaluation programs are developed by analysts familiar with the daily routine in a laboratory dedicated to pesticide residue analysis, the clear documentation of the macro commands and their capabilities are the basis for developing a powerful userfriendly macro program.
313
H.-J. Stan 6.10.1 Automated evaluation of full-scan acquisition data applying AuPest Screening analyses in the author's laboratory in the early 1990s, using the HP 5970 mass selective detector (MSD) with cyclic scanning and searching in a designated mass spectral pesticide library, gave surprisingly good results. Manual data evaluation still remained very time-consuming, although the search was only carried out in a designated library. Therefore, the macro programAuPest was developed in our laboratory to simulate automatically all the steps usually applied in manual data evaluation [29,30]. The program and its predecessors have been used successfully over the last 10 years or so for pesticide residue analysis in food and also various kinds of environmental analysis in ground and surface water as well as soil samples. AuPest, taking full advantage of WINDOWS M , follows the line an analyst would take in evaluating the mass spectral data acquired. Such an evaluation includes autointegration with automated peak recognition, background subtraction and library search in designated pesticide libraries and also in universal mass spectral libraries. The decision concerning the presence of a pesticide is supported by quality factors but needs final inspection by the analyst with a direct visual comparison of the mass spectrum of the suspect with that found in the library with the search routine. A very important feature is the use of actual or corrected retention times as a very important independent piece of information in pesticide recognition. This enables the recognition of target compounds overlapped by matrix compounds, which produce poor library search results. On the other hand, any similarity between the mass spectrum of the sample peak and the reference spectrum must be considered as purely coincidental if the retention times of the reference target compound and sample peak are significantly different. AuPest provides, when operated on its first level, a complete analysis report with all integrated peaks listed with their retention times and search results. In a second result table, called important peak list, only those results of the library search that have met user-defined thresholds for hit quality and retention time windows are compiled. A third result table contains the integration results of all peaks with such details as peak area, peak width, resolution, peak start and peak end. Together with the TIC picture, the integration results table presents an overview of all compounds detected in the sample, as shown in Fig. 6.17. Data processing is completed in the time needed by the GC/MSD system to cool down after a run with a temperature program and then equilibrate before the next start. A second advantage of AuPest Level 1 is that the analyst can check the results first on the screen and decide later what he wants to print out. 314
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Fig. 6.17. AuPest results of a tomato sample after automated evaluation. Right window: HP ChemStation Standalone Data Analysis with TIC chromatogram in window #2 and AuPest integrated in the task line with AuPest pull-down menu open. Left window: AuPest results with Level 1 and Level 2 results and the corresponding important peak lists.
This saves printing costs and reduces paper consumption enormously. Finally, the automatic comparison of search results with and without background subtraction always guarantees the best search results. As mentioned above, the AuPest Level 1 results table may contain some search results with a poor hit quality but excellent correlation in the retention times for the peak searched and the suggested library compound. In this case, the target compound may be overlapped by a co-eluate from the matrix and manual evaluation, therefore, is then required. Such a manual verification procedure, performed to confirm the identity of a compound generating a peak overlapped by the peak of a matrix compound, can provide excellent results when using RICs of appropriate selected ions as described in section 6.9.5. A disadvantage of this technique is that it is very time-consuming when applied to a great number of peaks. Therefore, AuPest Level 2 was developed to execute automatically all the steps described above.
315
H.-J. Stan The user has to create so-called "control files" that define two or three indicative ions and the time window for the target compounds. Level 2 begins to check for the first target compound by redrawing the specified ion traces in a user-defined time window, usually 1 min around the expected retention time of the target compound. Only if Level 2 has found peaks in the traces of the indicative ions will it proceed to check whether peaks appear at the same retention time in these ion traces. If their difference in retention is smaller than 0.015 min, Level 2 assumes that these ions originate from the same target compound and continues by sampling a scan at the apex of this peak followed by background subtraction. This is performed by subtracting the scans taken at peak start and peak end. A dedicated pesticide library is searched to find a match for the resulting spectrum. It can usually be seen when looking at the RIC traces that the apices of the target compound ion traces do not fit exactly the apices of the matrix compound peak. Therefore, the raw spectrum of the scan selected by Level 2 generally shows good correspondence to that of the target compound sought. Further background subtraction at peak start and peak end of the target compound may eliminate the interfering ions almost completely, so that the library search now results in a better hit quality. The library search is also performed without background subtraction. Only the better result is reported. Level 2 then continues to search for the next target compound listed in the control files that include a total search capacity of up to 500 target compounds. One particular feature of Level 2 is based on the RIC technique. Level 2 can find those peaks that are normally overlooked through being hidden in noise. These peaks are naturally not integrated by the integration software and, as a consequence, no search is carried out. Since the S/N ratio is, with most of the ion traces, orders of magnitudes better than with TIC, the presence of compounds can be spotted at very low concentration levels depending, of course, on the overall abundance of the fragment ions selected. An example is given in section 6.9.5 with the manual verification procedure. The development of AuPest was carried out using an older GC/MSD system. It turned out that the limits ofAuPest were bound by the instrumental limits of detection. With the newer generation of GC-MS systems having an increased detection sensitivity, automated evaluation of full-scan GC-MS analysis of food samples applying AuPest became the established procedure for screening analyses for pesticide residues in our laboratory. In the following, the application of AuPest to a sample of tomatoes with a few pesticide residues detected is described briefly. The whole procedure and the total number of pesticides included have been recently published [30]. 316
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