A. Abad et al., Monoclonal enzyme immunoassay for the analysis of carbaryl in fruits and vegetables without sample cleanup, J AGR FOOD, 49(4), 2001, pp. 1707-1712
The N-methylcarbamate pesticide carbaryl is one of the most important insec
ticides used worldwide. In the present work, the validation of a monoclonal
antibody-based enzyme immunoassay (ELISA) for the determination of this co
mpound in fruits and vegetables is described. The immunoassay is a competit
ive heterologous ELISA in the antibody-coated format, with an I-50 value fo
r standards in buffer of 101.0 +/- 26.9 ng/L and with a dynamic range betwe
en 31.6 and 364.0 ng/L. For recovery studies, peppers, cucumbers, strawberr
ies, tomatoes, potatoes, oranges, and apples were spiked with carbaryl at 1
0, 50, and 200 ppb. After liquid extraction, analyses were performed by ELI
SA on both extracts purified on solid-phase extraction (SPE) columns and cr
ude, nonpurified extracts. Depending on the crop and the fortification leve
l, recoveries in the 59.0-120.0% range were obtained for purified samples a
nd in the 70.0-137.7% range for crude extracts. The carbaryl immunoassay pe
rformance was further validated with respect to high-performance liquid chr
omatography (HPLC) with postcolumn derivatization and fluorescence detectio
n (EPA Method 531.1), Samples were spiked with carbaryl at several concentr
ations and analyzed as blind samples by ELISA and HPLC after SPE cleanup. T
he correlation between methods was excellent (y = 1.04x + 0.71, r(2) = 0.99
2, n = 33), with HPLC being more precise than ELISA (mean coefficients of v
ariation of 5.2 and 12.0%, respectively). The immunoassay was then applied
to the analysis of nonpurified extracts of the same samples. Results also c
ompared very well with those obtained by HPLC on purified samples (y = 1.28
x - 0.59, r(2) = 0.987, n = 33) while maintaining similar precision. Theref
ore, the developed immunoassay is a suitable method for the quantitative an
d reliable determination of carbaryl in fruits and vegetables even without
sample cleanup, which saves time and money and considerably increases sampl
e throughput.