Alan R. C. Hill

Unit-to-unit variability of pesticide residues in fruit and vegetables

Pesticide residue levels (36 pesticides and some of their metabolites) were determined in the individual units taken from large samples of apples, bananas, celery, kiwi fruit, oranges, peaches and nectarines, pears, plums, potatoes, and tomatoes. The 65 large samples (generally about 100–110 units, but only 45 units of celery) were purchased at retail or wholesale outlets in the UK. The lots from which the samples were drawn originated from 17 different countries. Average concentrations in the samples were in the approximate range 0.002-2 mg kg-1. Unit-to-unit variability factors (97.5th percentile mg kg-1/average mg kg-1), for the pesticide/product combination data sets in which >10% of samples contained measurable residues (n = 106), were in the range 1.4–9.6 (11.1 based on a value of zero for data below reporting limits). Analytical variance contributed only a small proportion (up to 11%) to the overall variance of the 106 data sets. There was no evidence of a relationship between the variability factor and the commodity, country of origin, residue concentration or the physicochemical characteristics of the pesticide. The extent of variability appears to be determined at or about the time of pesticide application. Taking non-detectable residues as half the reporting limits, the frequency distribution of variability factors was approximately log-normal, with a geometric mean of 3.4. The corresponding 95% probability limits of the variability factors were calculated to be 1.6 and 7.6.

Determination of residues of the plant growth regulator chlormequat in pears by ion-exchange high performance liquid chromatography-electrospray mass spectrometry†

We report a method which we have used routinely for the determination of chlormequat residues in pears. After extraction with methanol, determination was performed, without clean-up, by ion-exchange HPLC using an SCX column eluted with aqueous ammonium formate-methanol, and HPLC-MS with an electrospray interface. MS and MS-MS were employed concurrently, using selected ion monitoring and selected reaction monitoring, respectively, of the 35Cl and 37Cl isotopes of the chlormequat cation and the CID transitions of each of these precursors to the common product ion at m/z 58. The method was suitable for determinations at concentrations of chlormequat cation of 0.04 mg kg-1. Concentrations determined using the four signals were in good agreement (mean RSD 3%). The mean recovery of chlormequat cation at 0.16 mg kg-1, measured using the m/z 122-->58 signal, was 86% (RSD 7%) under repeatability conditions and 88% (RSD 15%) in routine application of the method over a 3 month period. Analysis of an in-house reference sample of pears, similarly analysed over the 3 month period, gave an RSD of 10% with a mean of 0.14 mg kg-1. Mean recovery at 0.016 mg kg-1, under repeatability conditions on two occasions, was 101% (RSD 6%) and 56% (RSD 12%).

Organophosphorus sulphides, sulphoxides and sulphones. Part 2. Characterisation by gas chromatography-mass spectrometry

The gas-chromatographic behaviour and electron-impact mass spectrometric characteristics are reported for nearly 90 organophosphorus sulphides, sulphoxides and sulphones, used as or derived from pesticides.

Residue variability and sampling practical problems and consequences for residues monitoring

Data generated in the UK have indicated that pesticide residue levels can be highly variable between the individual fruit or vegetables from the same crop or lot in trade. Statistical experiments with these data showed that residues in composite samples, taken according to Codex recommendations, are unlikely to differ by more than a factor of 3–4 from the mean level in the lot. This was corroborated by results obtained from real composite samples. Many fruit or vegetables in trade are mixed after harvest to form combined lots. Analysis of composite samples provides a good indication of average residues but, where the lot has been mixed, such average values are potentially misleading. Residues monitoring is the best means available for general control of pesticide use and consumer exposure, but new strategies for sampling and analysis are required to address the combined effects of residues variability and mixing of lots.

Organophosphorus sulphides, sulphoxides and sulphones. Part I. Determination of residues in fruit and vegetables by gas-liquid chromatography

Conditions have been established for the routine quantitative determination of residues of demephion, demeton-S-methyl, disulfoton, fenamiphos, fensulfothion, fenthion, phorate, terbufos, thiometon and their toxic metabolites following conversion into the sulphones. Packed column gas chromatography-mass spectrometry demonstrated that most of the sulphoxides tended to decompose under the conditions required for gas chromatography, whereas most of the sulphides and sulphones were unaffected by such conditions. Temephos and its metabolites and the metabolites of vamidothion decomposed completely during gas chromatography. Some suggestions are given for assessing and avoiding the column priming and enhancement problems often observed in the gas chromatography of these and other polar organophosphorus pesticides.

Occurrence and risks associated with chlormequat residues in a range of foodstuffs in the UK

Trends in the usage pattern of chlormequat (a plant growth regulator) on cereal crops in the UK over the past 6 years are presented. The figures have been supplemented by monitoring of chlormequat residues in food commodities through the UK surveillance programme, and for cereals, the carry-through into a number of processed cereal-based foods has been followed. A downward trend of chlormequat residue levels in pears sampled between 1997 and 2002 was observed. This decline reflects changes that were introduced in European and national regulations and which have proven to be extremely effective in reducing both the frequency of detection and levels of chlormequat residues. Both acute and chronic risk assessments were undertaken based on aggregate dietary exposure data. Even when the highest residues observed were used in the calculations, the assessments showed that both the short- and long-term intakes for all consumer groups would be unlikely to cause adverse health effects and were therefore not of any cause for concern.

A comparison of simple statistical methods for estimating analytical uncertainty, taking into account predicted frequency distributions

Error in chemical analysis is propagated mainly by multiplication (not addition) of random, systematic and spurious errors. Individual random errors tend to have symmetrical frequency distributions but their combined error distribution has a positive skew. Certain systematic errors (bias) conceivably could have frequency distributions which would enhance or lessen the overall skew but they are unlikely to produce a truly normal distribution. Each analytical method, or modification of it, may produce a unique frequency distribution of results. Hence an ideal general statistical treatment of results cannot exist and the best practical compromise should be utilised. Three simple statistical treatments of data produced from various analytical models were compared, to identify the best compromise. Conventional statistics, with no transformation of data, generally treated low results too favourably and high results too harshly. Prior transformation of results to logarithms tended to do the reverse. Transformation of results to factors, followed by derivation of a robust standard deviation, treated the extremes more equally, if somewhat harshly. Factor statistics for precision have low sensitivity to outliers and the assigned true value and they offer a good compromise for the description of analytical data.

Factor transformation to produce statistics describing the uncertainty of analytical data

Analytical uncertainty produced by random error has a positively skewed distribution and accuracy and precision have non-linear scales. Compared with conventional statistics, factor transformation of the data allows more appropriate interpretation of results and facilitates graphical inspection of data. Statistics are compared for practical examples of performance in proficiency tests and of repeatability and reproducibility in collaborative studies. Factor transformation is shown to be applicable to wide ranges of analyte concentration and measurement precision.

Chapter 1 Quality control for pesticide residues analysis

Publisher Summary This chapter discusses analytical quality control (AQC) for the pesticide residues analysis. The objective of AQC is to provide reassurance of fitness-for-purpose of the estimates or results generated. Consumer confidence, food-trade decisions, and regulatory controls depend on the quality of analyses. Determination of quantity can be divided into two aspects: (1) determination of whether a specific concentration limit has been exceeded and (2) determination of the absolute concentration. Analytical mistakes can be extremely costly in terms of lost trade, destruction of crops, fines for growers, and litigation against the analyst. AQC must therefore be rigorous but the challenging nature of the analyses creates conflicting requirements. The cost of the residues analysis is generally high, few of the techniques are rapid, and AQC requirements can contribute substantially to costs and time requirements.