Ultrasensitive detection of 2,4-dichlorophenoxyacetic acid by inhibiting alkaline phosphatase immobilized onto a highly porous gold nanocoral electrode

Herein, we describe the design and implementation of an ultrasensitive enzyme inhibition-based biosensor for 2,4-dichlorophenoxyacetic acid (2,4-D) detection. The biosensor utilizes alkaline phosphatase (AlP), immobilized on a photo-crosslinked polymer matrix of poly(vinyl alcohol) functionalized with <i>N</i>-methyl-4(4'-formylstyryl)pyridinium (PVA-SbQ), supported by electrodes coated with highly porous gold nanocorals (hPGNCs). After preliminary electrochemical and morphological characterization, the PVA-SbQ/AlP/hPGNC electrode was tested for inhibition studies employing ascorbate 2-phosphate (A2P) as the initial substrate. The biosensor preparation/sensing time from electrode preparation to final results is approximately 45 minutes, which enables the possibility to easily scale up the electrode production process on a daily basis with a reliable analytical result in only 5 minutes of amperometric measurement. Following the initial kinetic studies and evaluation of analytical performance, the PVA-SbQ/AlP/hPGNC platform demonstrated a linear detection range from 0.002 to 22 ppt, with a sensitivity of 0.121 ± 0.006 ppt^-1 (RSD = 4.9%, <i>R</i>² = 0.996, and <i>N</i> = 6) and a limit of detection (LoD) of 0.7 ppq. This sensitivity is 7-8 orders of magnitude below the regulatory thresholds in Europe and the USA. Furthermore, the biosensor was validated using 19 homogenized wheat leaf sample extracts, prepared in line with European Food Safety Authority (EFSA) guidelines, achieving average recoveries exceeding 96% and RSD values under 9.8%. The biosensor also exhibited robust operational and storage stability, maintaining 84% (30 hours of continuous operation) and 94% (120 days) of its initial response, respectively. These results highlight the potential of the PVA-SbQ/AlP/hPGNC biosensor for on-site 2,4-D monitoring in agricultural crops and its feasibility for integration with artificial intelligence for advanced diagnostics.