High-performance detection of nitrogen in soil using superhydrophobic-hydrophilic array and silver nano...

Rapid and accurate detection of nitrogen (N) in soil is crucial for assessing soil fertility levels and guiding precise fertilization. However, conventional chemical detection methods often involve complicated and time-consuming procedures. Herein, we developed a new method based on a superhydrophobic-hydrophilic array and nano dual-structure assisted molecular laser-induced breakdown spectroscopy (SHA-NDS-MLIBS) for detecting available N in soil. A hydrophilic array was fabricated on a superhydrophobic graphite substrate to concentrate the soil solution in the detection region. Two nanostructures of silver nanowires (Ag NWs) and silver nanoparticles (Ag NPs) were rationally aggregated to improve detection repeatability and sensitivity. The results revealed that a limit of detection (LOD) for soil-N was 0.92 mg/kg, with a relative standard deviation (RSD) of 6.58 %. Meanwhile, an artificial intelligence-driven adaptive boosting-random forest (AdaBoost-RF) model was developed to accurately predict soil-N levels, with a prediction set correlation coefficient (R_p²) of 0.9745. This study provides an innovative approach for high-performance detection of soil-N, contributing to smart agriculture and environmental protection.