Monoclonal enzyme immunoassay for the analysis of carbaryl in fruits and vegetables without sample cleanup

The N-methylcarbamate pesticide carbaryl is one of the most important insecticides used worldwide. In the present work, the validation of a monoclonal antibody-based enzyme immunoassay (ELISA) for the determination of this compound in fruits and vegetables is described. The immunoassay is a competitive heterologous ELISA in the antibody-coated format, with an I50 value for standards in buffer of 101.0 +/- 26.9 ng/L and with a dynamic range between 31.6 and 364.0 ng/L. For recovery studies, peppers, cucumbers, strawberries, tomatoes, potatoes, oranges, and apples were spiked with carbaryl at 10, 50, and 200 ppb. After liquid extraction, analyses were performed by ELISA on both extracts purified on solid-phase extraction (SPE) columns and crude, nonpurified extracts. Depending on the crop and the fortification level, recoveries in the 59.0-120.0% range were obtained for purified samples and in the 70.0-137.7% range for crude extracts. The carbaryl immunoassay performance was further validated with respect to high-performance liquid chromatography (HPLC) with postcolumn derivatization and fluorescence detection (EPA Method 531.1). Samples were spiked with carbaryl at several concentrations and analyzed as blind samples by ELISA and HPLC after SPE cleanup. The correlation between methods was excellent (y = 1.04x + 0.71, r2 = 0.992, n = 33), with HPLC being more precise than ELISA (mean coefficients of variation of 5.2 and 12.0%, respectively). The immunoassay was then applied to the analysis of nonpurified extracts of the same samples. Results also compared very well with those obtained by HPLC on purified samples (y = 1.28x - 0.59, r2 = 0.987, n = 33) while maintaining similar precision. Therefore, the developed immunoassay is a suitable method for the quantitative and reliable determination of carbaryl in fruits and vegetables even without sample cleanup, which saves time and money and considerably increases sample throughput.