Development of an immunochromatographic assay based on carbon nanoparticles for the determination of the phytoregulator forchlorfenuron

Rapid analytical methods enabling the determination of diverse targets are essential in a number of research areas, from clinical diagnostics to feed and food quality and safety. Herein, the development of a quantitative immunochromatographic assay for the detection of the synthetic phytoregulator forchlorfenuron (CPPU) is described. The competitive lateral flow immunoassay (LFIA) was based on the immobilization onto a nitrocellulose membrane of an ovalbumin–CPPU conjugate (test line) and on the use of an immunodetection ligand consisting of carbon nanoparticles labeled with an anti-CPPU monoclonal antibody through interaction with a secondary antibody. The presence of CPPU in horticultural samples was visually interpreted by the decrease in the black signal intensity of the test line, according to the competitive character of the format. The quantitative determination of the analyte was easily performed by a two-step procedure consisting of flatbed scanning of the strips followed by computer-based image analysis of the pixel gray volumes of the test lines. Under optimized conditions, the immunochromatographic test afforded a limit of quantification in buffer of 89 ng/L. The accuracy of the strip test was assessed by the analysis of fruit samples with incurred residues, and the obtained results were compared with those derived from two reference methods, ELISA and HPLC. The LOQ of the CPPU-specific LFIA in kiwifruits and grapes was established at 33.4 μg/kg. The excellent analytical performance of the developed strip test demonstrates the potential of immunochromatographic assays for the quantitative monitoring of small organic molecules in complex matrices.

► A rapid and sensitive strip test for CPPU (forchlorfenuron) detection is reported.
► Carbon nanoparticles were used for antibody labeling.
► A common flatbed scanner was employed to quantitate strip spots.
► The new method was successfully applied to the analysis of field samples.