Uncertainty of measurement of pesticide residues in vegetable products: application of alternative approaches based on quality control data for multi/single residue methods

Abstract

Measurement uncertainty is a non-negative parameter that characterizes the dispersion of the quantity values attributed to a measurand, based on the information used. This work outlines top-down evaluations of the measurement uncertainty in the analysis of pesticide residues by using precision and bias data. Since 2009, a European Standard for vegetable products has been issued which describes a multi-method for the analysis of pesticide residues in foods of plant origin such as fruits, vegetables and cereals. This method makes testing for hundreds of compounds quick and easy in a single extraction, but technical difficulties nevertheless have arisen in the highly polar pesticides in these specific cases; methods suitable for single pesticide residues are used. Consequently, we defined a workflow to estimate measurement uncertainty depending on method type selection. The calculation of individual Measurement Uncertainty (MU) may not always be possible for multi-residue method; then, an alternative approach was applied to estimate a generic MU using data from different proficiency tests selected for the three main product groups (fruit, vegetable and cereal) in combination with intra-laboratory precision. This approach shows a limitation due to the minimum number of proficiency test results that prevents their effective implementation in single residue methods. Therefore, a specific approach based on internal laboratory quality control for individual pesticides in a specific family group of products on real samples was applied to estimate the Measurement Uncertainty. The Flonicamid residue in vegetable products was the selected case study for the Single Residue Method.