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

Abstract

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.

Modelling non-systemic pesticide residues in fruits with initial deposit variability and weather effects

“…The model used a single CV value to estimate the 95% confidence intervals for the initial deposit for each zone. large (Harris and Davis 1998;Ambrus 2000;Harris 2000;Hill 2000;Hill and Reynolds 2002). The accurate prediction of acute dietary risks of pesticide residues in food also depends critically on an understanding of this variability.…”

Validation and sensitivity analysis of a probabilistic model for dietary exposure assessment to pesticide residues with a Basque Country duplicate diet study

“…In Europe, the discovery in the UK of the importance of the unit-to-unit variability in acute exposure assessments highlighted the benefits of probabilistic assessments (WHO 1997a, Crossley 2000, Hamey 2000, Harris et al 2002, Hill and Reynolds 2002. These probabilistic assessments are considered in the regulation procedure in the UK (PSD 2001) and subsequently are being revised by the European Union (EU).…”

Variability of organophosphorus insecticide residues in large size crops grown in commercial farms in Brazil

“…For all crop/pesticide combinations, more than 90% of the treated units had detected residues (>0.01 mg/kg), and for the calculation of the mean, residues <LOQ were replaced with Ý LOQ. Some authors have also used this approach (Hill and Reynolds 2002;Earl et al 2000), while others assumed the values at <LOQ as zero (Hamilton et al 2004). Ambrus (2000) has tested the effect of non-detectable residues and their LOQ on the calculation of the variability factor.…”