Journal
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
Volume 49, Issue 4, Pages 1713-1719Publisher
AMER CHEMICAL SOC
DOI: 10.1021/jf001171q
Keywords
immunoassay; ELISA; pesticide; N-methylcarbamates; HPLC; analysis; validation
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The N-methylcarbamate pesticide carbofuran is a very important insecticide used worldwide. In the present work, the validation of a monoclonal antibody-based enzyme immunoassay (ELISA) to determine this compound in fruits and vegetables is described. The immunoassay is a competitive heterologous ELISA in the antibody-coated format, with an I-50 value for standards in buffer of 740 ng/L and with a dynamic range between 200 and 3100 ng/L. For recovery studies, peppers, cucumbers, strawberries, tomatoes, potatoes, oranges, and apples were spiked with carbofuran at 10, 50, and 200 ppb. After liquid extraction, analyses were performed by ELISA on extracts purified on solid-phase extraction (SPE) columns and crude, nonpurified extracts. Depending on the crop, mean recoveries in the 43.9-90.7% range were obtained for purified samples and in the 90.1-121.6% range for crude extracts. The carbofuran 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 carbofuran at several concentrations and analyzed as blind samples by ELISA and HPLC after SPE cleanup. The correlation between methods was very good (y, = 0.90x + 2.66, r(2) = 0.958, n. = 25), with HPLC being more precise than ELISA (mean coefficients of variation of 4.1 and 11.5%, 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 = 1.02x + 10.44, r(2) = 0.933, n. = 29). Therefore, the developed immunoassay is a suitable method for the quantitative and reliable determination of carbofuran in fruits and vegetables even without sample cleanup, which saves time and money and considerably increases the sample throughput.
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